R/GgplotUtils.R
In GreenleafLab/ArchR: Analyzing single-cell regulatory chromatin in R.
Defines functions
ggPoint
Documented in
ggPoint
##########################################################################################
# ggplot2 Wrapper Methods For Easy Plotting
##########################################################################################
#' A ggplot-based dot plot wrapper function
#'
#' This function is a wrapper around ggplot geom_point to allow for a more intuitive plotting of ArchR data.
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param color A numeric/categorical vector used to determine the coloration for each point.
#' @param discrete A boolean value indicating whether the supplied data is discrete (`TRUE`) or continuous (`FALSE`).
#' @param discreteSet The name of a custom palette from `ArchRPalettes` to use for categorical/discrete color.
#' This argument is only used if `discrete` is set to `TRUE`.
#' @param continuousSet The name of a custom palette from `ArchRPalettes` to use for numeric color.
#' This argument is only used if `discrete` is set to `FALSE`.
#' @param labelMeans A boolean value indicating whether the mean of each categorical/discrete color should be labeled.
#' @param pal A custom palette used to override discreteSet/continuousSet for coloring vector.
#' @param defaultColor The default color for points that do not have another color applied (i.e. `NA` values).
#' @param highlightPoints A integer vector describing which points to hightlight. The remainder of points will be colored light gray.
#' @param colorDensity A boolean value indicating whether the density of points on the plot should be indicated by color.
#' If `TRUE`, continuousSet is used as the color palette.
#' @param size The numeric size of the points to be plotted.
#' @param xlim A numeric vector of two values indicating the lower and upper bounds of the x-axis on the plot.
#' @param ylim A numeric vector of two values indicating the lower and upper bounds of the y-axis on the plot.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum and minimum
#' values if `xlim` and `ylim` are not provided. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param randomize A boolean value indicating whether to randomize the order of the points when plotting.
#' @param seed A numeric seed number for use in randomization.
#' @param colorTitle A title to be added to the legend if `color` is supplied.
#' @param colorOrder A vector that allows you to control the order of palette colors associated with the values in `color`.
#' For example if you have `color` as `c("a","b","c")` and want to have the first color selected from the palette be used for
#' "c", the second color for "b", and the third color for "a", you would supply the `colorOrder` as `c("c", "b", "a")`.
#' @param colorLimits A numeric vector of two values indicating the lower and upper bounds of colors if numeric. Values
#' beyond these limits are thresholded.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param legendSize The size in inches to use for plotting the color legend.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param labelAsFactors A boolean indicating whether to label the `color` input as a numeric factor (`TRUE`) or with a character string (`FALSE`).
#' @param fgColor The foreground color of the plot.
#' @param bgColor The background color of the plot.
#' @param bgWidth The background relative width size of the halos in the labeling.
#' @param labelSize The numeric font size of labels.
#' @param addFit A string indicating the method to use for adding a fit/regression line to the plot (see `ggplot2::geom_smooth()` methods).
#' If set to `NULL`, no fit/regression line is added.
#' @param rastr A boolean value that indicates whether the plot should be rasterized using `ggrastr`. This does not rasterize
#' lines and labels, just the internal portions of the plot.
#' @param dpi The resolution in dots per inch to use for the plot.
#' @export
ggPoint <- function(
x = NULL,
y = NULL,
color = NULL,
discrete = TRUE,
discreteSet = "stallion",
continuousSet = "solarExtra",
labelMeans = TRUE,
pal = NULL,
defaultColor = "lightGrey",
highlightPoints = NULL,
colorDensity = FALSE,
size = 1,
xlim = NULL,
ylim = NULL,
extend = 0.05,
xlabel = "x",
ylabel = "y",
title = "",
randomize = FALSE,
seed = 1,
colorTitle = NULL,
colorOrder = NULL,
colorLimits = NULL,
alpha = 1,
baseSize = 10,
legendSize = 3,
ratioYX = 1,
labelAsFactors = TRUE,
fgColor = "black",
bgColor = "white",
bgWidth = 1,
labelSize = 3,
addFit = NULL,
rastr = FALSE,
dpi = 300,
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = color, name = "color", valid = c("numeric", "character", "null"))
.validInput(input = discrete, name = "discrete", valid = c("boolean"))
.validInput(input = discreteSet, name = "discreteSet", valid = c("character"))
.validInput(input = continuousSet, name = "continuousSet", valid = c("character"))
.validInput(input = labelMeans, name = "labelMeans", valid = c("boolean"))
.validInput(input = pal, name = "pal", valid = c("character", "null"))
.validInput(input = defaultColor, name = "defaultColor", valid = c("character"))
.validInput(input = highlightPoints, name = "highlightPoints", valid = c("integer", "null"))
.validInput(input = colorDensity, name = "colorDensity", valid = c("boolean"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = xlim, name = "xlim", valid = c("numeric", "null"))
.validInput(input = ylim, name = "ylim", valid = c("numeric", "null"))
.validInput(input = extend, name = "extend", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = randomize, name = "randomize", valid = c("boolean"))
.validInput(input = seed, name = "seed", valid = c("integer"))
.validInput(input = colorTitle, name = "colorTitle", valid = c("character", "null"))
.validInput(input = colorOrder, name = "colorOrder", valid = c("character", "null"))
.validInput(input = colorLimits, name = "colorLimits", valid = c("numeric", "null"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = legendSize, name = "legendSize", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric"))
.validInput(input = labelAsFactors, name = "labelAsFactors", valid = c("boolean"))
.validInput(input = fgColor, name = "fgColor", valid = c("character", "null"))
.validInput(input = bgColor, name = "bgColor", valid = c("character"))
.validInput(input = bgWidth, name = "bgWidth", valid = c("numeric"))
.validInput(input = labelSize, name = "labelSize", valid = c("numeric"))
.validInput(input = addFit, name = "addFit", valid = c("character", "null"))
.validInput(input = rastr, name = "rastr", valid = c("boolean"))
.validInput(input = dpi, name = "dpi", valid = c("numeric"))
stopifnot(length(y) == length(x))
if(length(x) < 5){
stop("x must be at least length 5 to plot!")
}
if(randomize){
set.seed(seed)
idx <- sample(seq_along(x), length(x))
}else{
idx <- seq_along(x)
}
df <- data.frame(x = x, y = y)
include <- which(is.finite(x) & is.finite(y))
if(length(include) != length(x)){
message("Some values are not finite! Excluding these points!")
df <- df[include,]
x <- x[include]
y <- y[include]
if(!is.null(color)){
color <- color[include]
}
}
if(is.null(xlim)){
xlim <- range(df$x) %>% extendrange(f = extend)
}
if(is.null(ylim)){
ylim <- range(df$y) %>% extendrange(f = extend)
}
ratioXY <- ratioYX * diff(xlim)/diff(ylim)
#Plot
.requirePackage("ggplot2", source = "cran")
if (is.null(color) & !colorDensity) {
p <- ggplot(df[idx,], aes(x = x, y = y)) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = F) +
xlab(xlabel) + ylab(ylabel) +
ggtitle(title) +
theme_ArchR(baseSize = baseSize)
if(rastr){
p <- p + .geom_point_rast2(
size = size, raster.dpi = dpi, alpha = alpha, color = defaultColor)
# if(!requireNamespace("ggrastr", quietly = TRUE)){
# message("ggrastr is not available for rastr of points, continuing without rastr!")
# p <- p + geom_point(size = size, alpha = alpha, color = defaultColor)
# }else{
# .requirePackage("ggrastr")
# p <- p + geom_point_rast(
# size = size, raster.dpi = dpi, alpha = alpha, color = defaultColor)
# }
}else{
p <- p + geom_point(size = size, alpha = alpha, color = defaultColor)
}
}else {
if(colorDensity){
discrete <- FALSE
df <- .getDensity(x, y, n = 100, sample = NULL) #change
df <- df[order(df$density), ,drop=FALSE]
df$color <- df$density
if(is.null(colorTitle)){
colorTitle <- "density"
}
}else if(discrete){
if(!is.null(highlightPoints)){
if(length(highlightPoints) < length(color)){
color[-highlightPoints] <- "Non.Highlighted"
idx <- c(idx[-highlightPoints], idx[highlightPoints])
}
}
color <- paste0(color)
if(!is.null(colorOrder)){
if(!all(color %in% colorOrder)){
stop("Not all colors are in colorOrder!")
}
}else{
colorOrder <- gtools::mixedsort(unique(color))
}
if(is.null(colorTitle)){
colorTitle <- "color"
}
stopifnot(length(color) == nrow(df))
df$color <- factor(color, levels = colorOrder)
if(labelAsFactors){
df$color <- factor(
x = paste0(paste0(match(paste0(df$color), paste0(levels(df$color)))), "-", paste0(df$color)),
levels = paste0(seq_along(levels(df$color)), "-", levels(df$color))
)
if(!is.null(pal)){
#print(pal)
#print(paste0(levels(df$color))[match(names(pal), colorOrder)])
names(pal) <- paste0(levels(df$color))[match(names(pal), colorOrder)]
}
colorOrder <- paste0(levels(df$color))
}
}else{
stopifnot(length(color) == nrow(df))
if(!is.null(highlightPoints)){
if(length(highlightPoints) < length(color)){
color[-highlightPoints] <- NA
idx <- c(idx[-highlightPoints], idx[highlightPoints])
}
}
if(!is.null(colorLimits)){
color[color < min(colorLimits)] <- min(colorLimits)
color[color > max(colorLimits)] <- max(colorLimits)
}
df$color <- color
}
p <- ggplot(df[idx,], aes(x = x, y = y, color = color)) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = FALSE) +
xlab(xlabel) + ylab(ylabel) +
ggtitle(title) + theme_ArchR(baseSize = baseSize) +
theme(legend.direction = "horizontal", legend.box.background = element_rect(color = NA)) +
labs(color = colorTitle)
if(rastr){
p <- p + .geom_point_rast2(
size = size, raster.dpi = dpi, alpha = alpha,
raster.width = min(par('fin')),
raster.height = (ratioYX * min(par('fin')))
)
# if(!requireNamespace("ggrastr", quietly = TRUE)){
# message("ggrastr is not available for rastr of points, continuing without rastr!")
# message("To install ggrastr try : devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point(size = size, alpha = alpha)
# }else{
# .requirePackage("ggrastr", installInfo = "devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point_rast(
# size = size, raster.dpi = dpi, alpha = alpha,
# raster.width=par('fin')[1],
# raster.height = (ratioYX * par('fin')[2])
# )
# }
}else{
p <- p + geom_point(size = size, alpha = alpha)
}
if (discrete) {
if (!is.null(pal)) {
p <- p + scale_color_manual(values = pal)
}else {
pal <- paletteDiscrete(set = discreteSet, values = colorOrder)
if(!is.null(highlightPoints)){
pal[grep("Non.Highlighted", names(pal))] <- "lightgrey"
}
#print(pal)
p <- p + scale_color_manual(values = pal) +
guides(color = guide_legend(override.aes = list(size = legendSize, shape = 15)))
}
if (labelMeans) {
dfMean <- split(df, df$color) %>% lapply(., function(x) {
data.frame(x = median(x[, 1]), y = median(x[, 2]), color = x[1, 3])
}) %>% Reduce("rbind", .)
if(labelAsFactors){
dfMean$label <- stringr::str_split(paste0(seq_len(nrow(dfMean))), pattern = "\\-", simplify=TRUE)[,1]
}else{
dfMean$label <- dfMean$color
}
dfMean$text <- stringr::str_split(dfMean$color, pattern = "-", simplify = TRUE)[,1]
# make halo layers, similar to https://github.com/GuangchuangYu/shadowtext/blob/master/R/shadowtext-grob.R#L43
theta <- seq(pi / 8, 2 * pi, length.out = 16)
xo <- bgWidth * diff(range(df$x)) / 300
yo <- bgWidth * diff(range(df$y)) / 300
for (i in theta) {
p <- p +
geom_text(data = dfMean,
aes_q(
x = bquote(x + .(cos(i) * xo)),
y = bquote(y + .(sin(i) * yo)),
label = ~text
),
size = labelSize,
color = bgColor
)
}
if(is.null(fgColor)){
p <- p + geom_text(data = dfMean, aes(x = x, y = y, color = color, label = label), size = labelSize, show.legend = FALSE)
}else{
p <- p + geom_text(data = dfMean, aes(x = x, y = y, label = label), color = fgColor, size = labelSize, show.legend = FALSE)
}
}
}else{
if (!is.null(pal)) {
if(!is.null(colorLimits)){
p <- p + scale_colour_gradientn(colors = pal, limits=colorLimits, na.value = "lightgrey")
}else{
p <- p + scale_colour_gradientn(colors = pal, na.value = "lightgrey")
}
}else {
if(!is.null(colorLimits)){
p <- p + scale_colour_gradientn(colors = paletteContinuous(set = continuousSet), limits=colorLimits, na.value = "lightgrey")
}else{
p <- p + scale_colour_gradientn(colors = paletteContinuous(set = continuousSet), na.value = "lightgrey")
}
}
}
}
if (!is.null(addFit)) {
p <- p + geom_smooth(data = df, aes(color = NULL), method = addFit, color = "black") +
ggtitle(paste0(title, "\nPearson = ", round(cor(df$x, df$y), 3), "\nSpearman = ", round(cor(df$x, df$y, method = "spearman"), 3)))
}
p <- p + theme(legend.position = "bottom", legend.key = element_rect(size = 2))#, legend.spacing.x = unit(0.1, 'cm'), legend.spacing.y = unit(0.1, 'cm'))
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
return(p)
}
#' A ggplot-based one-to-one dot plot wrapper function
#'
#' This function is a wrapper around ggplot geom_point to allow for plotting one-to-one sample comparisons in ArchR.
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param size The numeric size of the points to plot.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param min The lower limit of the x and y axes as a numeric quantile between 0 and 1.
#' @param max The upper limit of the x and y axes as a numeric quantile between 0 and 1.
#' @param nPlot The number of points to plot. When this value is less than the total points, the `sample` function is used to extract random data points to be plotted.
#' @param nKernel The number of grid points in each direction to use when computing the kernel with `MASS::kde2d()`.
#' @param densityMax The quantile that should be represented by the maximum color on the continuous scale designated by `pal`. Values above `densityMax` will be thresholded to the maximum color on the color scale.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum value on either axis. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end beyond `quantile(c(x,y), max)` and `quantile(c(x,y), min)`.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param rastr A boolean value that indicates whether the plot should be rasterized. This does not rasterize lines and labels, just the internal portions of the plot.
#' @param pal A custom palette from `ArchRPalettes` used to display the density of points on the plot.
#' @param ... Additional params to be supplied to ggPoint
#' @export
ggOneToOne <- function (
x = NULL,
y = NULL,
size = 2,
alpha = 1,
xlabel = "x",
ylabel = "y",
title = "Correlation",
min = 0.05,
max = 0.9999,
nPlot = 100 * 10^3,
nKernel = 100,
densityMax = 0.95,
extend = 0.05,
baseSize = 6,
rastr = TRUE,
pal = paletteContinuous(set = "blueYellow"),
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = min, name = "min", valid = c("numeric"))
.validInput(input = max, name = "max", valid = c("numeric"))
.validInput(input = nPlot, name = "nPlot", valid = c("integer"))
.validInput(input = nKernel, name = "nKernel", valid = c("numeric"))
.validInput(input = densityMax, name = "densityMax", valid = c("numeric"))
.validInput(input = extend, name = "extend", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = rastr, name = "rastr", valid = c("boolean"))
.validInput(input = pal, name = "pal", valid = c("character"))
#Check for NA
idx <- which(!is.na(x) & !is.na(y) & !is.infinite(x) & !is.infinite(y))
x <- x[idx]
y <- y[idx]
#Ratio X/Y
lim <- quantile(c(x, y), c(min, max)) %>% extendrange(f = extend)
ratioXY <- diff(lim)/diff(lim)
#Calculate Correlations
pearson <- round(cor(x, y, method = "pearson", use = "complete"), 3)
spearman <- round(cor(x, y, method = "spearman", use = "complete"), 3)
title <- sprintf("%s \nPearson = %s , Spearman = %s", title, pearson, spearman)
#Get Density
message("adding denisty..")
df <- .getDensity(x, y, n = nKernel, sample = nPlot) #change
df <- df[order(df[, "density"]), ]
#GGPlot
message("plotting..")
gg <- ggPoint(
x = df$x,
y = df$y,
color = df$density,
pal = pal,
xlabel = xlabel,
ylabel = ylabel,
discrete = FALSE,
colorTitle = "density",
xlim = lim,
ylim = lim,
size = size,
alpha = alpha,
title = title,
baseSize = baseSize,
rastr = rastr,
...
) + geom_abline(slope = 1, intercept = 0, lty = "dashed")
return(gg)
}
.getDensity <- function(x = NULL, y = NULL, n = 100, sample = NULL, densityMax = 0.95){
#modified from http://slowkow.com/notes/ggplot2-color-by-density/
df <- data.frame(x=x,y=y)
dens <- MASS::kde2d(x = x, y = y, n = n)
ix <- findInterval(x, dens$x)
iy <- findInterval(y, dens$y)
ii <- cbind(ix, iy)
df$density <- dens$z[ii]
df$density[df$density > quantile(unique(df$density),densityMax)] <- quantile(unique(df$density),densityMax) #make sure the higher end doesnt bias colors
if(!is.null(sample)){
df <- df[sample(nrow(df), min(sample,nrow(df))),]
}
return(df)
}
#' A ggplot-based Hexplot wrapper function summary of points in a standardized manner
#'
#' This function will plot x,y coordinate values summarized in hexagons in a standardized manner
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param color A numeric/categorical vector containing coloring information for each point.
#' @param pal A custom continuous palette from `ArchRPalettes` for coloration of hexes.
#' @param bins The number of bins to be used for plotting the hexplot. `bins` indicates the total number of hexagons that will fit within the surface area of the plot.
#' @param xlim A numeric vector of two values indicating the lower and upper bounds of the x-axis on the plot.
#' @param ylim A numeric vector of two values indicating the lower and upper bounds of the y-axis on the plot.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum and minimum values if `xlim` and `ylim` are not provided. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param colorTitle The label to use for the legend corresponding to `color`.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param FUN The function to use for summarizing data into hexagons. Typically "mean" or something similar.
#' @param hexCut If this is not null, a quantile cut is performed to threshold the top and bottom of the distribution of values.
#' This prevents skewed color scales caused by strong outliers. The format of this should be c(a,b) where `a` is the upper threshold
#' and `b` is the lower threshold. For example, hexCut = c(0.025,0.975) will take the top and bottom 2.5 percent of values and set
#' them to the value of the 97.5th and 2.5th percentile values respectively.
#' @param addPoints A boolean value indicating whether individual points should be shown on the hexplot.
#' @param ... Additional params for plotting
#' @export
ggHex <- function(
x = NULL,
y = NULL,
color = NULL,
pal = paletteContinuous(set = "solarExtra"),
bins = 200,
xlim = NULL,
ylim = NULL,
extend = 0.05,
xlabel = "x",
ylabel = "y",
title = "",
colorTitle = "values",
baseSize = 6,
ratioYX = 1,
FUN = "median",
hexCut = c(0.02, 0.98),
addPoints = FALSE,
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = color, name = "color", valid = c("numeric"))
.validInput(input = pal, name = "pal", valid = c("character"))
.validInput(input = bins, name = "bins", valid = c("integer"))
.validInput(input = xlim, name = "xlim", valid = c("numeric", "null"))
.validInput(input = ylim, name = "ylim", valid = c("numeric", "null"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = colorTitle, name = "colorTitle", valid = c("character", "null"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric"))
.validInput(input = FUN, name = "FUN", valid = c("character"))
.validInput(input = hexCut, name = "quantCut", valid = c("numeric", "null"))
.validInput(input = addPoints, name = "addPoints", valid = c("boolean"))
#require hexbin to be installed. otherwise, this section wont work properly
.requirePackage(x = "hexbin", source = "CRAN")
df <- data.frame(x = x, y = y)
include <- which(is.finite(x) & is.finite(y))
if(length(include) != length(x)){
message("Some values are not finite! Excluding these points!")
df <- df[include,]
if(!is.null(color)){
color <- color[include]
}
}
df$color <- color
if (is.null(xlim)) {
xlim <- range(df$x) %>% extendrange(f = extend)
}
if (is.null(ylim)) {
ylim <- range(df$y) %>% extendrange(f = extend)
}
ratioXY <- ratioYX * diff(xlim)/diff(ylim)
p <- ggplot()
if(addPoints){
p <- p + .geom_point_rast2(data = df, aes(x=x,y=y), color = "lightgrey")
# if(requireNamespace("ggrastr", quietly = TRUE)){
# .requirePackage("ggrastr", installInfo = "devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point_rast(data = df, aes(x=x,y=y), color = "lightgrey")
# }else{
# message("ggrastr is not available for rastr of points, continuing without points!")
# message("To install ggrastr try : devtools::install_github('VPetukhov/ggrastr')")
#}
}
values <- ggplot_build(p + stat_summary_hex(data = df, aes(x=x,y=y,z=color), fun = FUN, bins = bins, color = NA))$data[[1]]$value
if(!is.null(hexCut)){
limits <- quantile(values, c(min(hexCut), max(hexCut)), na.rm=TRUE)
}else{
limits <- c(min(values), max(values))
}
p <- p + stat_summary_hex(data = df, aes(x=x,y=y,z=color), fun = FUN, bins = bins, color = NA) +
scale_fill_gradientn(
colors = pal,
limits = limits,
oob = scales::squish
) +
xlab(xlabel) +
ylab(ylabel) +
ggtitle(title) +
theme_ArchR(baseSize = baseSize) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = FALSE) +
theme(legend.direction="horizontal", legend.box.background = element_rect(color = NA)) +
labs(fill = colorTitle)
p <- p + theme(legend.position = "bottom")
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
p
}
#' A ggplot-based ridge/violin plot wrapper function
#'
#' This function is a wrapper around ggplot geom_density_ridges or geom_violin to allow for plotting group distribution plots in ArchR.
#'
#' @param x A character vector containing the categorical x-axis values for each y-axis value.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param groupOrder A character vector indicating a custom order for plotting x-axis categorical values. Should contain all possible
#' values of `x` in the desired order.
#' @param groupSort A boolean indicating whether to sort groups based on the average value of the group.
#' @param size The line width for boxplot/summary lines.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param ridgeScale A numeric indicating the relative size for each ridge in the ridgeplot.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param title The title of the plot.
#' @param pal A named custom palette (see `paletteDiscrete()` and `ArchRPalettes`) for discrete coloring.
#' @param addBoxPlot A boolean indicating whether to add a boxplot to the plot if `plotAs="violin"`.
#' @param plotAs A string indicating how the groups should be plotted. Acceptable values are "ridges" (for a `ggrides`-style plot) or "violin" (for a violin plot).
#' @param ... Additional parameters to pass to `ggplot2` for plotting.
#' @export
ggGroup <- function(
x = NULL,
y = NULL,
xlabel = NULL,
ylabel = NULL,
groupOrder = NULL,
groupSort = FALSE,
size = 1,
baseSize = 10,
ridgeScale = 1,
ratioYX = NULL,
alpha = 1,
title = "",
pal = paletteDiscrete(values=x, set = "stallion"),
addBoxPlot = TRUE,
plotAs = "ridges",
...
){
.validInput(input = x, name = "x", valid = c("character"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character", "null"))
.validInput(input = ylabel, name = "ylabel", valid = c("character", "null"))
.validInput(input = groupOrder, name = "groupOrder", valid = c("character", "null"))
.validInput(input = groupSort, name = "groupSort", valid = c("boolean"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = ridgeScale, name = "ridgeScale", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric", "null"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = pal, name = "pal", valid = c("character"))
.validInput(input = addBoxPlot, name = "addBoxPlot", valid = c("boolean"))
.validInput(input = plotAs, name = "plotAs", valid = c("character"))
names(y) <- x
dm <- stats::aggregate(y ~ names(y), FUN = mean)
df <- data.frame(x, y)
if(!is.null(groupOrder)){
if(!all(x %in% groupOrder)){
stop("Not all x values are present in groupOrder!")
}
}else{
if(groupSort){
groupOrder <- paste0(dm[,1])[order(dm[,2], decreasing= FALSE)]
}else{
if(tolower(plotAs) == "ridges"){
groupOrder <- rev(gtools::mixedsort(unique(x)))
}else{
groupOrder <- gtools::mixedsort(unique(x))
}
}
}
df$x <- factor(df$x, groupOrder)
p <- ggplot(df, aes(x = x, y = y, color = x)) +
scale_color_manual(values = pal, guide = "none") +
scale_fill_manual(values = pal, guide = "none") +
ggtitle(title)
if(tolower(plotAs) == "ridges" | tolower(plotAs) == "ggridges"){
if(!requireNamespace("ggridges", quietly = TRUE)){
type <- "violin"
message("ggridges is not available for plotting, continuing with geom_violin!")
message("To install ggridges try : install.packages('ggridges')")
p <- p + geom_violin(aes_string(fill="x"), alpha = alpha)
}else{
type <- "ridges"
.requirePackage("ggridges", source = "cran")
#p <- p +
# stat_density_ridges(aes_string(x = "y", y = "x", fill = "x"),
# quantile_lines = TRUE, quantiles = c(0.5), alpha = alpha, color = "black",
# scale = ridgeScale
# ) + scale_y_discrete(expand = c(0, 0))
# stat_density_ridges(
# aes_string(x = "y", y = "x", fill = "x"),
# quantile_lines = TRUE,
# alpha = alpha,
# geom = "density_ridges_gradient",
# calc_ecdf = TRUE,
# quantiles = c(0.5)
# )
val <- 1/length(unique(x))
p <- p + geom_density_ridges(data = df,
aes(x = y, y = x, color = x, fill = x), scale = ridgeScale,
alpha = alpha, color = "black") + scale_y_discrete(expand = expansion(mult = c(0.01, val)))
}
}else{
type <- "violin"
p <- p + geom_violin(aes_string(x = "x", y = "y", color = "x", fill="x"), alpha = alpha)
}
if(addBoxPlot & type == "violin"){
p <- p + geom_boxplot(size = size, outlier.size = 0, outlier.stroke = 0, fill = NA)
}
if(type != "violin"){
p <- p + theme_ArchR(baseSize = baseSize)
}else{
p <- p + theme_ArchR(xText90 = TRUE, baseSize = baseSize)
}
if(!is.null(ratioYX)){
p <- p + coord_fixed(ratioYX, expand = TRUE)
}
if (!is.null(xlabel)) {
if(type=="violin"){
p <- p + xlab(xlabel)
}else{
p <- p + xlab(ylabel)
}
}
if (!is.null(ylabel)) {
if(type=="violin"){
p <- p + ylab(ylabel)
}else{
p <- p + ylab(xlabel)
}
}
p <- p + theme(legend.position = "bottom")
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
return(p)
}
#' Align ggplot plots vertically or horizontally
#'
#' This function aligns ggplots vertically or horizontally
#'
#' @param ... All additional arguments will be interpreted as `ggplot2` plot objects and used if and only if `plotList` is `NULL`
#' @param plotList A list of `ggplot2` plot objects to be aligned.
#' @param sizes A numeric vector or list of values indicating the relative size for each of the objects in `plotList` or supplied in `...`. If the plot is supplied in `...` the order is the same as the input in this function. If set to NULL all plots will be evenly distributed.
#' @param type A string indicating wheter vertical ("v") or horizontal ("h") alignment should be used for the multi-plot layout.
#' @param draw A boolean value indicating whether to draw the plot(s) (`TRUE`) or return a graphical object (`FALSE`).
#' @export
ggAlignPlots <- function(
...,
plotList = NULL,
sizes = NULL,
type = "v",
draw = TRUE
){
.validInput(input = plotList, name = "plotList", valid = c("list", "null"))
.validInput(input = sizes, name = "sizes", valid = c("numeric", "null"))
.validInput(input = type, name = "type", valid = c("character"))
.validInput(input = draw, name = "draw", valid = c("boolean"))
if(type %ni% c("v", "h")){
stop("type must be v (vertical) or h (horizontal)!")
}
#http://stackoverflow.com/a/21503904
.requirePackage("gtable", source = "cran")
if(is.null(plotList)){
plotList <- list(...)
}
## test that only passing plots
stopifnot(do.call(all, lapply(plotList, inherits, "gg")))
gl <- lapply(plotList, ggplotGrob)
#if ncols do not match fill with empty gtables_add_cols
if(type == "v" | type == "vertical"){
maxCol <- max(unlist(lapply(gl, ncol)))
gl <- lapply(gl, function(x){
while(ncol(x) < max(maxCol)){
x <- gtable::gtable_add_cols(x, unit(1, "null"))
}
return(x)
})
}
combined <- Reduce(function(x, y)
if(type == "v" | type == "vertical"){
gtable:::rbind_gtable(x,y,"first")
}else{
gtable:::cbind_gtable(x,y,"first")
}, gl[-1], gl[[1]])
if(type == "v" | type == "vertical"){
combined$widths <- do.call(grid::unit.pmax, lapply(gl, "[[", "widths"))
#remove vertical spaces from background layout
combined$heights[combined$layout$t[grepl("background", combined$layout$name)][-1]] <- grid::unit(rep(0,length(combined$heights[combined$layout$t[grepl("background", combined$layout$name)][-1]])), "cm")
if(!missing(sizes)){
sList <- lapply(seq_along(gl), function(x){
orig <- gl[[x]]$heights[gl[[x]]$layout$t[grepl("panel", gl[[x]]$layout$name)]]
new <- rep(sizes[[x]]/length(orig),length(orig))
return(new)
})
s <- grid::unit(unlist(sList), "null")
combined$heights[combined$layout$t[grepl("panel", combined$layout$name)]] <- s
}
}else if(type == "h" | type == "horizontal"){
combined$heights <- do.call(grid::unit.pmax, lapply(gl, "[[", "heights"))
if(!missing(sizes)){
sList <- lapply(seq_along(gl), function(x){
orig <- gl[[x]]$widths[gl[[x]]$layout$l[grepl("panel", gl[[x]]$layout$name)]]
new <- rep(sizes[[x]]/length(orig),length(orig))
return(new)
})
s <- grid::unit(unlist(sList), "null")
combined$widths[combined$layout$l[grepl("panel", combined$layout$name)]] <- s
}
}else{
stop("Unrecognized type ", type)
}
if(draw){
grid::grid.newpage()
grid::grid.draw(combined)
}else{
combined
}
}
#' ggplot2 default theme for ArchR
#'
#' This function returns a ggplot2 theme that is black borded with black font.
#'
#' @param color The color to be used for text, lines, ticks, etc for the plot.
#' @param textFamily The font default family to be used for the plot.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param baseLineSize The base line width (in points) to be used throughout the plot.
#' @param baseRectSize The base line width (in points) to use for rectangular boxes throughout the plot.
#' @param plotMarginCm The width in centimeters of the whitespace margin around the plot.
#' @param legendPosition The location to put the legend. Valid options are "bottom", "top", "left", and "right.
#' @param legendTextSize The base text size (in points) for the legend text.
#' @param axisTickCm The length in centimeters to be used for the axis ticks.
#' @param xText90 A boolean value indicating whether the x-axis text should be rotated 90 degrees counterclockwise.
#' @param yText90 A boolean value indicating whether the y-axis text should be rotated 90 degrees counterclockwise.
#' @export
theme_ArchR <- function(
color = "black",
textFamily = "sans",
baseSize = 10,
baseLineSize = 0.5,
baseRectSize = 0.5,
plotMarginCm = 1,
legendPosition = "bottom",
legendTextSize = 5,
axisTickCm = 0.1,
xText90 = FALSE,
yText90 = FALSE
){
.validInput(input = color, name = "color", valid = c("character"))
.validInput(input = textFamily, name = "textFamily", valid = c("character"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = baseLineSize, name = "baseLineSize", valid = c("numeric"))
.validInput(input = baseRectSize, name = "baseRectSize", valid = c("numeric"))
.validInput(input = plotMarginCm, name = "plotMarginCm", valid = c("numeric"))
.validInput(input = legendPosition, name = "legendPosition", valid = c("character"))
.validInput(input = legendTextSize, name = "legendTextSize", valid = c("numeric"))
.validInput(input = axisTickCm, name = "axisTickCm", valid = c("numeric"))
.validInput(input = xText90, name = "xText90", valid = c("boolean"))
.validInput(input = yText90, name = "yText90", valid = c("boolean"))
theme <- theme_bw() + theme(
text = element_text(family = textFamily),
axis.text = element_text(color = color, size = baseSize),
axis.title = element_text(color = color, size = baseSize),
title = element_text(color = color, size = baseSize),
plot.margin = unit(c(plotMarginCm, plotMarginCm, plotMarginCm, plotMarginCm), "cm"),
panel.background = element_rect(fill = "transparent", colour = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_rect(fill = NA, color = color, size = (4/3) * baseRectSize * as.numeric(grid::convertX(grid::unit(1, "points"), "mm"))),
axis.ticks.length = unit(axisTickCm, "cm"),
axis.ticks = element_line(color = color, size = baseLineSize * (4/3) * as.numeric(grid::convertX(grid::unit(1, "points"), "mm"))),
legend.key = element_rect(fill = "transparent", colour = NA),
legend.text = element_text(color = color, size = legendTextSize),
legend.box.background = element_rect(color = NA),
#legend.box.background = element_rect(fill = "transparent"),
legend.position = legendPosition,
strip.text = element_text(size = baseSize, color="black")#,
#plot.background = element_rect(fill = "transparent", color = NA)
)
if(xText90){
theme <- theme %+replace% theme(axis.text.x = element_text(angle = 90, hjust = 1))
}
if(yText90){
theme <- theme %+replace% theme(axis.text.y = element_text(angle = 90, vjust = 1))
}
return(theme)
}
##########################################################################################
# ggplot2 helper functions
##########################################################################################
.checkCairo <- function(){
tryCatch({
tmp <- dev.cur()
Cairo::Cairo(type='raster')
dev.off()
dev.set(tmp)
TRUE
}, error = function(e){
FALSE
})
}
## Adapted from
## https://github.com/tidyverse/ggplot2/blob/660aad2db2b3495ae0d8040915a40d247133ffc0/R/geom-point.r
## from https://github.com/VPetukhov/ggrastr/blob/master/R/geom-point-rast.R
## This funciton now handles issues with Cairo installation that can lead to plot errors
.geom_point_rast2 <- function(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
raster.width = min(par('fin')),
raster.height = min(par('fin')),
raster.dpi = 300
){
GeomPointRast <- tryCatch({
if(!.checkCairo()){
stop()
}
#Try to create a geom rast for points if not then just use normal geom_point
ggplot2::ggproto(
"GeomPointRast",
ggplot2::GeomPoint,
required_aes = c("x", "y"),
non_missing_aes = c("size", "shape", "colour"),
default_aes = aes(
shape = 19, colour = "black", size = 1.5, fill = NA,
alpha = NA, stroke = 0.5
),
draw_panel = function(data, panel_params, coord, na.rm = FALSE,
raster.width=min(par('fin')), raster.height=min(par('fin')), raster.dpi=300){
#From ggrastr
prevDevID <- dev.cur()
p <- ggplot2::GeomPoint$draw_panel(data, panel_params, coord)
devID <- Cairo::Cairo(
type='raster',
width=raster.width*raster.dpi,
height=raster.height*raster.dpi,
dpi=raster.dpi,
units='px',
bg="transparent"
)[1]
grid::pushViewport(grid::viewport(width=1, height=1))
grid::grid.points(
x=p$x,
y=p$y,
pch = p$pch,
size = p$size,
name = p$name,
gp = p$gp,
vp = p$vp,
draw = TRUE
)
grid::popViewport()
gridCapture <- grid::grid.cap()
dev.off(devID)
dev.set(prevDevID)
grid::rasterGrob(
gridCapture,
x=0,
y=0,
width = 1,
height = 1,
default.units = "native",
just = c("left","bottom")
)
}
)
}, error = function(e){
if(.checkCairo()){
message("WARNING: Error found with trying to rasterize geom. Continuing without rasterization.")
}else{
message("WARNING: Error found with Cairo installation. Continuing without rasterization.")
}
#Default geom_point
ggplot2::ggproto(
"GeomPoint",
ggplot2::GeomPoint,
required_aes = c("x", "y"),
non_missing_aes = c("size", "shape", "colour"),
default_aes = aes(
shape = 19, colour = "black", size = 1.5, fill = NA,
alpha = NA, stroke = 0.5
),
draw_panel = function(data, panel_params, coord, na.rm = FALSE,
raster.width=min(par('fin')), raster.height=min(par('fin')), raster.dpi=300){
if (is.character(data$shape)) {
data$shape <- ggplot2:::translate_shape_string(data$shape) #Hidden ggplot2
}
coords <- coord$transform(data, panel_params)
pGrob <- grid::pointsGrob(
x = coords$x,
y = coords$y,
pch = coords$shape,
gp = grid::gpar(
col = scales::alpha(coords$colour, coords$alpha),
fill = scales::alpha(coords$fill, coords$alpha),
# Stroke is added around the outside of the point
fontsize = coords$size * .pt + coords$stroke * .stroke / 2,
lwd = coords$stroke * .stroke / 2
)
)
pGrob
},
draw_key = ggplot2::draw_key_point
)
})
ggplot2::layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomPointRast,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
raster.width=raster.width,
raster.height=raster.height,
raster.dpi=raster.dpi,
...
)
)
}
GreenleafLab/ArchR documentation built on Feb. 28, 2024, 4:17 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions ggPoint
Documented in ggPoint
##########################################################################################
# ggplot2 Wrapper Methods For Easy Plotting
##########################################################################################
#' A ggplot-based dot plot wrapper function
#'
#' This function is a wrapper around ggplot geom_point to allow for a more intuitive plotting of ArchR data.
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param color A numeric/categorical vector used to determine the coloration for each point.
#' @param discrete A boolean value indicating whether the supplied data is discrete (`TRUE`) or continuous (`FALSE`).
#' @param discreteSet The name of a custom palette from `ArchRPalettes` to use for categorical/discrete color.
#' This argument is only used if `discrete` is set to `TRUE`.
#' @param continuousSet The name of a custom palette from `ArchRPalettes` to use for numeric color.
#' This argument is only used if `discrete` is set to `FALSE`.
#' @param labelMeans A boolean value indicating whether the mean of each categorical/discrete color should be labeled.
#' @param pal A custom palette used to override discreteSet/continuousSet for coloring vector.
#' @param defaultColor The default color for points that do not have another color applied (i.e. `NA` values).
#' @param highlightPoints A integer vector describing which points to hightlight. The remainder of points will be colored light gray.
#' @param colorDensity A boolean value indicating whether the density of points on the plot should be indicated by color.
#' If `TRUE`, continuousSet is used as the color palette.
#' @param size The numeric size of the points to be plotted.
#' @param xlim A numeric vector of two values indicating the lower and upper bounds of the x-axis on the plot.
#' @param ylim A numeric vector of two values indicating the lower and upper bounds of the y-axis on the plot.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum and minimum
#' values if `xlim` and `ylim` are not provided. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param randomize A boolean value indicating whether to randomize the order of the points when plotting.
#' @param seed A numeric seed number for use in randomization.
#' @param colorTitle A title to be added to the legend if `color` is supplied.
#' @param colorOrder A vector that allows you to control the order of palette colors associated with the values in `color`.
#' For example if you have `color` as `c("a","b","c")` and want to have the first color selected from the palette be used for
#' "c", the second color for "b", and the third color for "a", you would supply the `colorOrder` as `c("c", "b", "a")`.
#' @param colorLimits A numeric vector of two values indicating the lower and upper bounds of colors if numeric. Values
#' beyond these limits are thresholded.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param legendSize The size in inches to use for plotting the color legend.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param labelAsFactors A boolean indicating whether to label the `color` input as a numeric factor (`TRUE`) or with a character string (`FALSE`).
#' @param fgColor The foreground color of the plot.
#' @param bgColor The background color of the plot.
#' @param bgWidth The background relative width size of the halos in the labeling.
#' @param labelSize The numeric font size of labels.
#' @param addFit A string indicating the method to use for adding a fit/regression line to the plot (see `ggplot2::geom_smooth()` methods).
#' If set to `NULL`, no fit/regression line is added.
#' @param rastr A boolean value that indicates whether the plot should be rasterized using `ggrastr`. This does not rasterize
#' lines and labels, just the internal portions of the plot.
#' @param dpi The resolution in dots per inch to use for the plot.
#' @export
ggPoint <- function(
x = NULL,
y = NULL,
color = NULL,
discrete = TRUE,
discreteSet = "stallion",
continuousSet = "solarExtra",
labelMeans = TRUE,
pal = NULL,
defaultColor = "lightGrey",
highlightPoints = NULL,
colorDensity = FALSE,
size = 1,
xlim = NULL,
ylim = NULL,
extend = 0.05,
xlabel = "x",
ylabel = "y",
title = "",
randomize = FALSE,
seed = 1,
colorTitle = NULL,
colorOrder = NULL,
colorLimits = NULL,
alpha = 1,
baseSize = 10,
legendSize = 3,
ratioYX = 1,
labelAsFactors = TRUE,
fgColor = "black",
bgColor = "white",
bgWidth = 1,
labelSize = 3,
addFit = NULL,
rastr = FALSE,
dpi = 300,
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = color, name = "color", valid = c("numeric", "character", "null"))
.validInput(input = discrete, name = "discrete", valid = c("boolean"))
.validInput(input = discreteSet, name = "discreteSet", valid = c("character"))
.validInput(input = continuousSet, name = "continuousSet", valid = c("character"))
.validInput(input = labelMeans, name = "labelMeans", valid = c("boolean"))
.validInput(input = pal, name = "pal", valid = c("character", "null"))
.validInput(input = defaultColor, name = "defaultColor", valid = c("character"))
.validInput(input = highlightPoints, name = "highlightPoints", valid = c("integer", "null"))
.validInput(input = colorDensity, name = "colorDensity", valid = c("boolean"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = xlim, name = "xlim", valid = c("numeric", "null"))
.validInput(input = ylim, name = "ylim", valid = c("numeric", "null"))
.validInput(input = extend, name = "extend", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = randomize, name = "randomize", valid = c("boolean"))
.validInput(input = seed, name = "seed", valid = c("integer"))
.validInput(input = colorTitle, name = "colorTitle", valid = c("character", "null"))
.validInput(input = colorOrder, name = "colorOrder", valid = c("character", "null"))
.validInput(input = colorLimits, name = "colorLimits", valid = c("numeric", "null"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = legendSize, name = "legendSize", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric"))
.validInput(input = labelAsFactors, name = "labelAsFactors", valid = c("boolean"))
.validInput(input = fgColor, name = "fgColor", valid = c("character", "null"))
.validInput(input = bgColor, name = "bgColor", valid = c("character"))
.validInput(input = bgWidth, name = "bgWidth", valid = c("numeric"))
.validInput(input = labelSize, name = "labelSize", valid = c("numeric"))
.validInput(input = addFit, name = "addFit", valid = c("character", "null"))
.validInput(input = rastr, name = "rastr", valid = c("boolean"))
.validInput(input = dpi, name = "dpi", valid = c("numeric"))
stopifnot(length(y) == length(x))
if(length(x) < 5){
stop("x must be at least length 5 to plot!")
}
if(randomize){
set.seed(seed)
idx <- sample(seq_along(x), length(x))
}else{
idx <- seq_along(x)
}
df <- data.frame(x = x, y = y)
include <- which(is.finite(x) & is.finite(y))
if(length(include) != length(x)){
message("Some values are not finite! Excluding these points!")
df <- df[include,]
x <- x[include]
y <- y[include]
if(!is.null(color)){
color <- color[include]
}
}
if(is.null(xlim)){
xlim <- range(df$x) %>% extendrange(f = extend)
}
if(is.null(ylim)){
ylim <- range(df$y) %>% extendrange(f = extend)
}
ratioXY <- ratioYX * diff(xlim)/diff(ylim)
#Plot
.requirePackage("ggplot2", source = "cran")
if (is.null(color) & !colorDensity) {
p <- ggplot(df[idx,], aes(x = x, y = y)) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = F) +
xlab(xlabel) + ylab(ylabel) +
ggtitle(title) +
theme_ArchR(baseSize = baseSize)
if(rastr){
p <- p + .geom_point_rast2(
size = size, raster.dpi = dpi, alpha = alpha, color = defaultColor)
# if(!requireNamespace("ggrastr", quietly = TRUE)){
# message("ggrastr is not available for rastr of points, continuing without rastr!")
# p <- p + geom_point(size = size, alpha = alpha, color = defaultColor)
# }else{
# .requirePackage("ggrastr")
# p <- p + geom_point_rast(
# size = size, raster.dpi = dpi, alpha = alpha, color = defaultColor)
# }
}else{
p <- p + geom_point(size = size, alpha = alpha, color = defaultColor)
}
}else {
if(colorDensity){
discrete <- FALSE
df <- .getDensity(x, y, n = 100, sample = NULL) #change
df <- df[order(df$density), ,drop=FALSE]
df$color <- df$density
if(is.null(colorTitle)){
colorTitle <- "density"
}
}else if(discrete){
if(!is.null(highlightPoints)){
if(length(highlightPoints) < length(color)){
color[-highlightPoints] <- "Non.Highlighted"
idx <- c(idx[-highlightPoints], idx[highlightPoints])
}
}
color <- paste0(color)
if(!is.null(colorOrder)){
if(!all(color %in% colorOrder)){
stop("Not all colors are in colorOrder!")
}
}else{
colorOrder <- gtools::mixedsort(unique(color))
}
if(is.null(colorTitle)){
colorTitle <- "color"
}
stopifnot(length(color) == nrow(df))
df$color <- factor(color, levels = colorOrder)
if(labelAsFactors){
df$color <- factor(
x = paste0(paste0(match(paste0(df$color), paste0(levels(df$color)))), "-", paste0(df$color)),
levels = paste0(seq_along(levels(df$color)), "-", levels(df$color))
)
if(!is.null(pal)){
#print(pal)
#print(paste0(levels(df$color))[match(names(pal), colorOrder)])
names(pal) <- paste0(levels(df$color))[match(names(pal), colorOrder)]
}
colorOrder <- paste0(levels(df$color))
}
}else{
stopifnot(length(color) == nrow(df))
if(!is.null(highlightPoints)){
if(length(highlightPoints) < length(color)){
color[-highlightPoints] <- NA
idx <- c(idx[-highlightPoints], idx[highlightPoints])
}
}
if(!is.null(colorLimits)){
color[color < min(colorLimits)] <- min(colorLimits)
color[color > max(colorLimits)] <- max(colorLimits)
}
df$color <- color
}
p <- ggplot(df[idx,], aes(x = x, y = y, color = color)) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = FALSE) +
xlab(xlabel) + ylab(ylabel) +
ggtitle(title) + theme_ArchR(baseSize = baseSize) +
theme(legend.direction = "horizontal", legend.box.background = element_rect(color = NA)) +
labs(color = colorTitle)
if(rastr){
p <- p + .geom_point_rast2(
size = size, raster.dpi = dpi, alpha = alpha,
raster.width = min(par('fin')),
raster.height = (ratioYX * min(par('fin')))
)
# if(!requireNamespace("ggrastr", quietly = TRUE)){
# message("ggrastr is not available for rastr of points, continuing without rastr!")
# message("To install ggrastr try : devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point(size = size, alpha = alpha)
# }else{
# .requirePackage("ggrastr", installInfo = "devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point_rast(
# size = size, raster.dpi = dpi, alpha = alpha,
# raster.width=par('fin')[1],
# raster.height = (ratioYX * par('fin')[2])
# )
# }
}else{
p <- p + geom_point(size = size, alpha = alpha)
}
if (discrete) {
if (!is.null(pal)) {
p <- p + scale_color_manual(values = pal)
}else {
pal <- paletteDiscrete(set = discreteSet, values = colorOrder)
if(!is.null(highlightPoints)){
pal[grep("Non.Highlighted", names(pal))] <- "lightgrey"
}
#print(pal)
p <- p + scale_color_manual(values = pal) +
guides(color = guide_legend(override.aes = list(size = legendSize, shape = 15)))
}
if (labelMeans) {
dfMean <- split(df, df$color) %>% lapply(., function(x) {
data.frame(x = median(x[, 1]), y = median(x[, 2]), color = x[1, 3])
}) %>% Reduce("rbind", .)
if(labelAsFactors){
dfMean$label <- stringr::str_split(paste0(seq_len(nrow(dfMean))), pattern = "\\-", simplify=TRUE)[,1]
}else{
dfMean$label <- dfMean$color
}
dfMean$text <- stringr::str_split(dfMean$color, pattern = "-", simplify = TRUE)[,1]
# make halo layers, similar to https://github.com/GuangchuangYu/shadowtext/blob/master/R/shadowtext-grob.R#L43
theta <- seq(pi / 8, 2 * pi, length.out = 16)
xo <- bgWidth * diff(range(df$x)) / 300
yo <- bgWidth * diff(range(df$y)) / 300
for (i in theta) {
p <- p +
geom_text(data = dfMean,
aes_q(
x = bquote(x + .(cos(i) * xo)),
y = bquote(y + .(sin(i) * yo)),
label = ~text
),
size = labelSize,
color = bgColor
)
}
if(is.null(fgColor)){
p <- p + geom_text(data = dfMean, aes(x = x, y = y, color = color, label = label), size = labelSize, show.legend = FALSE)
}else{
p <- p + geom_text(data = dfMean, aes(x = x, y = y, label = label), color = fgColor, size = labelSize, show.legend = FALSE)
}
}
}else{
if (!is.null(pal)) {
if(!is.null(colorLimits)){
p <- p + scale_colour_gradientn(colors = pal, limits=colorLimits, na.value = "lightgrey")
}else{
p <- p + scale_colour_gradientn(colors = pal, na.value = "lightgrey")
}
}else {
if(!is.null(colorLimits)){
p <- p + scale_colour_gradientn(colors = paletteContinuous(set = continuousSet), limits=colorLimits, na.value = "lightgrey")
}else{
p <- p + scale_colour_gradientn(colors = paletteContinuous(set = continuousSet), na.value = "lightgrey")
}
}
}
}
if (!is.null(addFit)) {
p <- p + geom_smooth(data = df, aes(color = NULL), method = addFit, color = "black") +
ggtitle(paste0(title, "\nPearson = ", round(cor(df$x, df$y), 3), "\nSpearman = ", round(cor(df$x, df$y, method = "spearman"), 3)))
}
p <- p + theme(legend.position = "bottom", legend.key = element_rect(size = 2))#, legend.spacing.x = unit(0.1, 'cm'), legend.spacing.y = unit(0.1, 'cm'))
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
return(p)
}
#' A ggplot-based one-to-one dot plot wrapper function
#'
#' This function is a wrapper around ggplot geom_point to allow for plotting one-to-one sample comparisons in ArchR.
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param size The numeric size of the points to plot.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param min The lower limit of the x and y axes as a numeric quantile between 0 and 1.
#' @param max The upper limit of the x and y axes as a numeric quantile between 0 and 1.
#' @param nPlot The number of points to plot. When this value is less than the total points, the `sample` function is used to extract random data points to be plotted.
#' @param nKernel The number of grid points in each direction to use when computing the kernel with `MASS::kde2d()`.
#' @param densityMax The quantile that should be represented by the maximum color on the continuous scale designated by `pal`. Values above `densityMax` will be thresholded to the maximum color on the color scale.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum value on either axis. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end beyond `quantile(c(x,y), max)` and `quantile(c(x,y), min)`.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param rastr A boolean value that indicates whether the plot should be rasterized. This does not rasterize lines and labels, just the internal portions of the plot.
#' @param pal A custom palette from `ArchRPalettes` used to display the density of points on the plot.
#' @param ... Additional params to be supplied to ggPoint
#' @export
ggOneToOne <- function (
x = NULL,
y = NULL,
size = 2,
alpha = 1,
xlabel = "x",
ylabel = "y",
title = "Correlation",
min = 0.05,
max = 0.9999,
nPlot = 100 * 10^3,
nKernel = 100,
densityMax = 0.95,
extend = 0.05,
baseSize = 6,
rastr = TRUE,
pal = paletteContinuous(set = "blueYellow"),
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = min, name = "min", valid = c("numeric"))
.validInput(input = max, name = "max", valid = c("numeric"))
.validInput(input = nPlot, name = "nPlot", valid = c("integer"))
.validInput(input = nKernel, name = "nKernel", valid = c("numeric"))
.validInput(input = densityMax, name = "densityMax", valid = c("numeric"))
.validInput(input = extend, name = "extend", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = rastr, name = "rastr", valid = c("boolean"))
.validInput(input = pal, name = "pal", valid = c("character"))
#Check for NA
idx <- which(!is.na(x) & !is.na(y) & !is.infinite(x) & !is.infinite(y))
x <- x[idx]
y <- y[idx]
#Ratio X/Y
lim <- quantile(c(x, y), c(min, max)) %>% extendrange(f = extend)
ratioXY <- diff(lim)/diff(lim)
#Calculate Correlations
pearson <- round(cor(x, y, method = "pearson", use = "complete"), 3)
spearman <- round(cor(x, y, method = "spearman", use = "complete"), 3)
title <- sprintf("%s \nPearson = %s , Spearman = %s", title, pearson, spearman)
#Get Density
message("adding denisty..")
df <- .getDensity(x, y, n = nKernel, sample = nPlot) #change
df <- df[order(df[, "density"]), ]
#GGPlot
message("plotting..")
gg <- ggPoint(
x = df$x,
y = df$y,
color = df$density,
pal = pal,
xlabel = xlabel,
ylabel = ylabel,
discrete = FALSE,
colorTitle = "density",
xlim = lim,
ylim = lim,
size = size,
alpha = alpha,
title = title,
baseSize = baseSize,
rastr = rastr,
...
) + geom_abline(slope = 1, intercept = 0, lty = "dashed")
return(gg)
}
.getDensity <- function(x = NULL, y = NULL, n = 100, sample = NULL, densityMax = 0.95){
#modified from http://slowkow.com/notes/ggplot2-color-by-density/
df <- data.frame(x=x,y=y)
dens <- MASS::kde2d(x = x, y = y, n = n)
ix <- findInterval(x, dens$x)
iy <- findInterval(y, dens$y)
ii <- cbind(ix, iy)
df$density <- dens$z[ii]
df$density[df$density > quantile(unique(df$density),densityMax)] <- quantile(unique(df$density),densityMax) #make sure the higher end doesnt bias colors
if(!is.null(sample)){
df <- df[sample(nrow(df), min(sample,nrow(df))),]
}
return(df)
}
#' A ggplot-based Hexplot wrapper function summary of points in a standardized manner
#'
#' This function will plot x,y coordinate values summarized in hexagons in a standardized manner
#'
#' @param x A numeric vector containing the x-axis values for each point.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param color A numeric/categorical vector containing coloring information for each point.
#' @param pal A custom continuous palette from `ArchRPalettes` for coloration of hexes.
#' @param bins The number of bins to be used for plotting the hexplot. `bins` indicates the total number of hexagons that will fit within the surface area of the plot.
#' @param xlim A numeric vector of two values indicating the lower and upper bounds of the x-axis on the plot.
#' @param ylim A numeric vector of two values indicating the lower and upper bounds of the y-axis on the plot.
#' @param extend A numeric value indicating the fraction to extend the x-axis and y-axis beyond the maximum and minimum values if `xlim` and `ylim` are not provided. For example, 0.05 will extend the x-axis and y-axis by 5 percent on each end.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param title The title of the plot.
#' @param colorTitle The label to use for the legend corresponding to `color`.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param FUN The function to use for summarizing data into hexagons. Typically "mean" or something similar.
#' @param hexCut If this is not null, a quantile cut is performed to threshold the top and bottom of the distribution of values.
#' This prevents skewed color scales caused by strong outliers. The format of this should be c(a,b) where `a` is the upper threshold
#' and `b` is the lower threshold. For example, hexCut = c(0.025,0.975) will take the top and bottom 2.5 percent of values and set
#' them to the value of the 97.5th and 2.5th percentile values respectively.
#' @param addPoints A boolean value indicating whether individual points should be shown on the hexplot.
#' @param ... Additional params for plotting
#' @export
ggHex <- function(
x = NULL,
y = NULL,
color = NULL,
pal = paletteContinuous(set = "solarExtra"),
bins = 200,
xlim = NULL,
ylim = NULL,
extend = 0.05,
xlabel = "x",
ylabel = "y",
title = "",
colorTitle = "values",
baseSize = 6,
ratioYX = 1,
FUN = "median",
hexCut = c(0.02, 0.98),
addPoints = FALSE,
...
){
.validInput(input = x, name = "x", valid = c("numeric"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = color, name = "color", valid = c("numeric"))
.validInput(input = pal, name = "pal", valid = c("character"))
.validInput(input = bins, name = "bins", valid = c("integer"))
.validInput(input = xlim, name = "xlim", valid = c("numeric", "null"))
.validInput(input = ylim, name = "ylim", valid = c("numeric", "null"))
.validInput(input = xlabel, name = "xlabel", valid = c("character"))
.validInput(input = ylabel, name = "ylabel", valid = c("character"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = colorTitle, name = "colorTitle", valid = c("character", "null"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric"))
.validInput(input = FUN, name = "FUN", valid = c("character"))
.validInput(input = hexCut, name = "quantCut", valid = c("numeric", "null"))
.validInput(input = addPoints, name = "addPoints", valid = c("boolean"))
#require hexbin to be installed. otherwise, this section wont work properly
.requirePackage(x = "hexbin", source = "CRAN")
df <- data.frame(x = x, y = y)
include <- which(is.finite(x) & is.finite(y))
if(length(include) != length(x)){
message("Some values are not finite! Excluding these points!")
df <- df[include,]
if(!is.null(color)){
color <- color[include]
}
}
df$color <- color
if (is.null(xlim)) {
xlim <- range(df$x) %>% extendrange(f = extend)
}
if (is.null(ylim)) {
ylim <- range(df$y) %>% extendrange(f = extend)
}
ratioXY <- ratioYX * diff(xlim)/diff(ylim)
p <- ggplot()
if(addPoints){
p <- p + .geom_point_rast2(data = df, aes(x=x,y=y), color = "lightgrey")
# if(requireNamespace("ggrastr", quietly = TRUE)){
# .requirePackage("ggrastr", installInfo = "devtools::install_github('VPetukhov/ggrastr')")
# p <- p + geom_point_rast(data = df, aes(x=x,y=y), color = "lightgrey")
# }else{
# message("ggrastr is not available for rastr of points, continuing without points!")
# message("To install ggrastr try : devtools::install_github('VPetukhov/ggrastr')")
#}
}
values <- ggplot_build(p + stat_summary_hex(data = df, aes(x=x,y=y,z=color), fun = FUN, bins = bins, color = NA))$data[[1]]$value
if(!is.null(hexCut)){
limits <- quantile(values, c(min(hexCut), max(hexCut)), na.rm=TRUE)
}else{
limits <- c(min(values), max(values))
}
p <- p + stat_summary_hex(data = df, aes(x=x,y=y,z=color), fun = FUN, bins = bins, color = NA) +
scale_fill_gradientn(
colors = pal,
limits = limits,
oob = scales::squish
) +
xlab(xlabel) +
ylab(ylabel) +
ggtitle(title) +
theme_ArchR(baseSize = baseSize) +
coord_equal(ratio = ratioXY, xlim = xlim, ylim = ylim, expand = FALSE) +
theme(legend.direction="horizontal", legend.box.background = element_rect(color = NA)) +
labs(fill = colorTitle)
p <- p + theme(legend.position = "bottom")
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
p
}
#' A ggplot-based ridge/violin plot wrapper function
#'
#' This function is a wrapper around ggplot geom_density_ridges or geom_violin to allow for plotting group distribution plots in ArchR.
#'
#' @param x A character vector containing the categorical x-axis values for each y-axis value.
#' @param y A numeric vector containing the y-axis values for each point.
#' @param xlabel The label to plot for the x-axis.
#' @param ylabel The label to plot for the y-axis.
#' @param groupOrder A character vector indicating a custom order for plotting x-axis categorical values. Should contain all possible
#' values of `x` in the desired order.
#' @param groupSort A boolean indicating whether to sort groups based on the average value of the group.
#' @param size The line width for boxplot/summary lines.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param ridgeScale A numeric indicating the relative size for each ridge in the ridgeplot.
#' @param ratioYX The aspect ratio of the x and y axes on the plot.
#' @param alpha A number indicating the transparency to use for each point. See `ggplot2` for more details.
#' @param title The title of the plot.
#' @param pal A named custom palette (see `paletteDiscrete()` and `ArchRPalettes`) for discrete coloring.
#' @param addBoxPlot A boolean indicating whether to add a boxplot to the plot if `plotAs="violin"`.
#' @param plotAs A string indicating how the groups should be plotted. Acceptable values are "ridges" (for a `ggrides`-style plot) or "violin" (for a violin plot).
#' @param ... Additional parameters to pass to `ggplot2` for plotting.
#' @export
ggGroup <- function(
x = NULL,
y = NULL,
xlabel = NULL,
ylabel = NULL,
groupOrder = NULL,
groupSort = FALSE,
size = 1,
baseSize = 10,
ridgeScale = 1,
ratioYX = NULL,
alpha = 1,
title = "",
pal = paletteDiscrete(values=x, set = "stallion"),
addBoxPlot = TRUE,
plotAs = "ridges",
...
){
.validInput(input = x, name = "x", valid = c("character"))
.validInput(input = y, name = "y", valid = c("numeric"))
.validInput(input = xlabel, name = "xlabel", valid = c("character", "null"))
.validInput(input = ylabel, name = "ylabel", valid = c("character", "null"))
.validInput(input = groupOrder, name = "groupOrder", valid = c("character", "null"))
.validInput(input = groupSort, name = "groupSort", valid = c("boolean"))
.validInput(input = size, name = "size", valid = c("numeric"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = ridgeScale, name = "ridgeScale", valid = c("numeric"))
.validInput(input = ratioYX, name = "ratioYX", valid = c("numeric", "null"))
.validInput(input = alpha, name = "alpha", valid = c("numeric"))
.validInput(input = title, name = "title", valid = c("character"))
.validInput(input = pal, name = "pal", valid = c("character"))
.validInput(input = addBoxPlot, name = "addBoxPlot", valid = c("boolean"))
.validInput(input = plotAs, name = "plotAs", valid = c("character"))
names(y) <- x
dm <- stats::aggregate(y ~ names(y), FUN = mean)
df <- data.frame(x, y)
if(!is.null(groupOrder)){
if(!all(x %in% groupOrder)){
stop("Not all x values are present in groupOrder!")
}
}else{
if(groupSort){
groupOrder <- paste0(dm[,1])[order(dm[,2], decreasing= FALSE)]
}else{
if(tolower(plotAs) == "ridges"){
groupOrder <- rev(gtools::mixedsort(unique(x)))
}else{
groupOrder <- gtools::mixedsort(unique(x))
}
}
}
df$x <- factor(df$x, groupOrder)
p <- ggplot(df, aes(x = x, y = y, color = x)) +
scale_color_manual(values = pal, guide = "none") +
scale_fill_manual(values = pal, guide = "none") +
ggtitle(title)
if(tolower(plotAs) == "ridges" | tolower(plotAs) == "ggridges"){
if(!requireNamespace("ggridges", quietly = TRUE)){
type <- "violin"
message("ggridges is not available for plotting, continuing with geom_violin!")
message("To install ggridges try : install.packages('ggridges')")
p <- p + geom_violin(aes_string(fill="x"), alpha = alpha)
}else{
type <- "ridges"
.requirePackage("ggridges", source = "cran")
#p <- p +
# stat_density_ridges(aes_string(x = "y", y = "x", fill = "x"),
# quantile_lines = TRUE, quantiles = c(0.5), alpha = alpha, color = "black",
# scale = ridgeScale
# ) + scale_y_discrete(expand = c(0, 0))
# stat_density_ridges(
# aes_string(x = "y", y = "x", fill = "x"),
# quantile_lines = TRUE,
# alpha = alpha,
# geom = "density_ridges_gradient",
# calc_ecdf = TRUE,
# quantiles = c(0.5)
# )
val <- 1/length(unique(x))
p <- p + geom_density_ridges(data = df,
aes(x = y, y = x, color = x, fill = x), scale = ridgeScale,
alpha = alpha, color = "black") + scale_y_discrete(expand = expansion(mult = c(0.01, val)))
}
}else{
type <- "violin"
p <- p + geom_violin(aes_string(x = "x", y = "y", color = "x", fill="x"), alpha = alpha)
}
if(addBoxPlot & type == "violin"){
p <- p + geom_boxplot(size = size, outlier.size = 0, outlier.stroke = 0, fill = NA)
}
if(type != "violin"){
p <- p + theme_ArchR(baseSize = baseSize)
}else{
p <- p + theme_ArchR(xText90 = TRUE, baseSize = baseSize)
}
if(!is.null(ratioYX)){
p <- p + coord_fixed(ratioYX, expand = TRUE)
}
if (!is.null(xlabel)) {
if(type=="violin"){
p <- p + xlab(xlabel)
}else{
p <- p + xlab(ylabel)
}
}
if (!is.null(ylabel)) {
if(type=="violin"){
p <- p + ylab(ylabel)
}else{
p <- p + ylab(xlabel)
}
}
p <- p + theme(legend.position = "bottom")
if(!is.null(ratioYX)){
attr(p, "ratioYX") <- ratioYX
}
return(p)
}
#' Align ggplot plots vertically or horizontally
#'
#' This function aligns ggplots vertically or horizontally
#'
#' @param ... All additional arguments will be interpreted as `ggplot2` plot objects and used if and only if `plotList` is `NULL`
#' @param plotList A list of `ggplot2` plot objects to be aligned.
#' @param sizes A numeric vector or list of values indicating the relative size for each of the objects in `plotList` or supplied in `...`. If the plot is supplied in `...` the order is the same as the input in this function. If set to NULL all plots will be evenly distributed.
#' @param type A string indicating wheter vertical ("v") or horizontal ("h") alignment should be used for the multi-plot layout.
#' @param draw A boolean value indicating whether to draw the plot(s) (`TRUE`) or return a graphical object (`FALSE`).
#' @export
ggAlignPlots <- function(
...,
plotList = NULL,
sizes = NULL,
type = "v",
draw = TRUE
){
.validInput(input = plotList, name = "plotList", valid = c("list", "null"))
.validInput(input = sizes, name = "sizes", valid = c("numeric", "null"))
.validInput(input = type, name = "type", valid = c("character"))
.validInput(input = draw, name = "draw", valid = c("boolean"))
if(type %ni% c("v", "h")){
stop("type must be v (vertical) or h (horizontal)!")
}
#http://stackoverflow.com/a/21503904
.requirePackage("gtable", source = "cran")
if(is.null(plotList)){
plotList <- list(...)
}
## test that only passing plots
stopifnot(do.call(all, lapply(plotList, inherits, "gg")))
gl <- lapply(plotList, ggplotGrob)
#if ncols do not match fill with empty gtables_add_cols
if(type == "v" | type == "vertical"){
maxCol <- max(unlist(lapply(gl, ncol)))
gl <- lapply(gl, function(x){
while(ncol(x) < max(maxCol)){
x <- gtable::gtable_add_cols(x, unit(1, "null"))
}
return(x)
})
}
combined <- Reduce(function(x, y)
if(type == "v" | type == "vertical"){
gtable:::rbind_gtable(x,y,"first")
}else{
gtable:::cbind_gtable(x,y,"first")
}, gl[-1], gl[[1]])
if(type == "v" | type == "vertical"){
combined$widths <- do.call(grid::unit.pmax, lapply(gl, "[[", "widths"))
#remove vertical spaces from background layout
combined$heights[combined$layout$t[grepl("background", combined$layout$name)][-1]] <- grid::unit(rep(0,length(combined$heights[combined$layout$t[grepl("background", combined$layout$name)][-1]])), "cm")
if(!missing(sizes)){
sList <- lapply(seq_along(gl), function(x){
orig <- gl[[x]]$heights[gl[[x]]$layout$t[grepl("panel", gl[[x]]$layout$name)]]
new <- rep(sizes[[x]]/length(orig),length(orig))
return(new)
})
s <- grid::unit(unlist(sList), "null")
combined$heights[combined$layout$t[grepl("panel", combined$layout$name)]] <- s
}
}else if(type == "h" | type == "horizontal"){
combined$heights <- do.call(grid::unit.pmax, lapply(gl, "[[", "heights"))
if(!missing(sizes)){
sList <- lapply(seq_along(gl), function(x){
orig <- gl[[x]]$widths[gl[[x]]$layout$l[grepl("panel", gl[[x]]$layout$name)]]
new <- rep(sizes[[x]]/length(orig),length(orig))
return(new)
})
s <- grid::unit(unlist(sList), "null")
combined$widths[combined$layout$l[grepl("panel", combined$layout$name)]] <- s
}
}else{
stop("Unrecognized type ", type)
}
if(draw){
grid::grid.newpage()
grid::grid.draw(combined)
}else{
combined
}
}
#' ggplot2 default theme for ArchR
#'
#' This function returns a ggplot2 theme that is black borded with black font.
#'
#' @param color The color to be used for text, lines, ticks, etc for the plot.
#' @param textFamily The font default family to be used for the plot.
#' @param baseSize The base font size (in points) to use in the plot.
#' @param baseLineSize The base line width (in points) to be used throughout the plot.
#' @param baseRectSize The base line width (in points) to use for rectangular boxes throughout the plot.
#' @param plotMarginCm The width in centimeters of the whitespace margin around the plot.
#' @param legendPosition The location to put the legend. Valid options are "bottom", "top", "left", and "right.
#' @param legendTextSize The base text size (in points) for the legend text.
#' @param axisTickCm The length in centimeters to be used for the axis ticks.
#' @param xText90 A boolean value indicating whether the x-axis text should be rotated 90 degrees counterclockwise.
#' @param yText90 A boolean value indicating whether the y-axis text should be rotated 90 degrees counterclockwise.
#' @export
theme_ArchR <- function(
color = "black",
textFamily = "sans",
baseSize = 10,
baseLineSize = 0.5,
baseRectSize = 0.5,
plotMarginCm = 1,
legendPosition = "bottom",
legendTextSize = 5,
axisTickCm = 0.1,
xText90 = FALSE,
yText90 = FALSE
){
.validInput(input = color, name = "color", valid = c("character"))
.validInput(input = textFamily, name = "textFamily", valid = c("character"))
.validInput(input = baseSize, name = "baseSize", valid = c("numeric"))
.validInput(input = baseLineSize, name = "baseLineSize", valid = c("numeric"))
.validInput(input = baseRectSize, name = "baseRectSize", valid = c("numeric"))
.validInput(input = plotMarginCm, name = "plotMarginCm", valid = c("numeric"))
.validInput(input = legendPosition, name = "legendPosition", valid = c("character"))
.validInput(input = legendTextSize, name = "legendTextSize", valid = c("numeric"))
.validInput(input = axisTickCm, name = "axisTickCm", valid = c("numeric"))
.validInput(input = xText90, name = "xText90", valid = c("boolean"))
.validInput(input = yText90, name = "yText90", valid = c("boolean"))
theme <- theme_bw() + theme(
text = element_text(family = textFamily),
axis.text = element_text(color = color, size = baseSize),
axis.title = element_text(color = color, size = baseSize),
title = element_text(color = color, size = baseSize),
plot.margin = unit(c(plotMarginCm, plotMarginCm, plotMarginCm, plotMarginCm), "cm"),
panel.background = element_rect(fill = "transparent", colour = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_rect(fill = NA, color = color, size = (4/3) * baseRectSize * as.numeric(grid::convertX(grid::unit(1, "points"), "mm"))),
axis.ticks.length = unit(axisTickCm, "cm"),
axis.ticks = element_line(color = color, size = baseLineSize * (4/3) * as.numeric(grid::convertX(grid::unit(1, "points"), "mm"))),
legend.key = element_rect(fill = "transparent", colour = NA),
legend.text = element_text(color = color, size = legendTextSize),
legend.box.background = element_rect(color = NA),
#legend.box.background = element_rect(fill = "transparent"),
legend.position = legendPosition,
strip.text = element_text(size = baseSize, color="black")#,
#plot.background = element_rect(fill = "transparent", color = NA)
)
if(xText90){
theme <- theme %+replace% theme(axis.text.x = element_text(angle = 90, hjust = 1))
}
if(yText90){
theme <- theme %+replace% theme(axis.text.y = element_text(angle = 90, vjust = 1))
}
return(theme)
}
##########################################################################################
# ggplot2 helper functions
##########################################################################################
.checkCairo <- function(){
tryCatch({
tmp <- dev.cur()
Cairo::Cairo(type='raster')
dev.off()
dev.set(tmp)
TRUE
}, error = function(e){
FALSE
})
}
## Adapted from
## https://github.com/tidyverse/ggplot2/blob/660aad2db2b3495ae0d8040915a40d247133ffc0/R/geom-point.r
## from https://github.com/VPetukhov/ggrastr/blob/master/R/geom-point-rast.R
## This funciton now handles issues with Cairo installation that can lead to plot errors
.geom_point_rast2 <- function(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
raster.width = min(par('fin')),
raster.height = min(par('fin')),
raster.dpi = 300
){
GeomPointRast <- tryCatch({
if(!.checkCairo()){
stop()
}
#Try to create a geom rast for points if not then just use normal geom_point
ggplot2::ggproto(
"GeomPointRast",
ggplot2::GeomPoint,
required_aes = c("x", "y"),
non_missing_aes = c("size", "shape", "colour"),
default_aes = aes(
shape = 19, colour = "black", size = 1.5, fill = NA,
alpha = NA, stroke = 0.5
),
draw_panel = function(data, panel_params, coord, na.rm = FALSE,
raster.width=min(par('fin')), raster.height=min(par('fin')), raster.dpi=300){
#From ggrastr
prevDevID <- dev.cur()
p <- ggplot2::GeomPoint$draw_panel(data, panel_params, coord)
devID <- Cairo::Cairo(
type='raster',
width=raster.width*raster.dpi,
height=raster.height*raster.dpi,
dpi=raster.dpi,
units='px',
bg="transparent"
)[1]
grid::pushViewport(grid::viewport(width=1, height=1))
grid::grid.points(
x=p$x,
y=p$y,
pch = p$pch,
size = p$size,
name = p$name,
gp = p$gp,
vp = p$vp,
draw = TRUE
)
grid::popViewport()
gridCapture <- grid::grid.cap()
dev.off(devID)
dev.set(prevDevID)
grid::rasterGrob(
gridCapture,
x=0,
y=0,
width = 1,
height = 1,
default.units = "native",
just = c("left","bottom")
)
}
)
}, error = function(e){
if(.checkCairo()){
message("WARNING: Error found with trying to rasterize geom. Continuing without rasterization.")
}else{
message("WARNING: Error found with Cairo installation. Continuing without rasterization.")
}
#Default geom_point
ggplot2::ggproto(
"GeomPoint",
ggplot2::GeomPoint,
required_aes = c("x", "y"),
non_missing_aes = c("size", "shape", "colour"),
default_aes = aes(
shape = 19, colour = "black", size = 1.5, fill = NA,
alpha = NA, stroke = 0.5
),
draw_panel = function(data, panel_params, coord, na.rm = FALSE,
raster.width=min(par('fin')), raster.height=min(par('fin')), raster.dpi=300){
if (is.character(data$shape)) {
data$shape <- ggplot2:::translate_shape_string(data$shape) #Hidden ggplot2
}
coords <- coord$transform(data, panel_params)
pGrob <- grid::pointsGrob(
x = coords$x,
y = coords$y,
pch = coords$shape,
gp = grid::gpar(
col = scales::alpha(coords$colour, coords$alpha),
fill = scales::alpha(coords$fill, coords$alpha),
# Stroke is added around the outside of the point
fontsize = coords$size * .pt + coords$stroke * .stroke / 2,
lwd = coords$stroke * .stroke / 2
)
)
pGrob
},
draw_key = ggplot2::draw_key_point
)
})
ggplot2::layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomPointRast,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
raster.width=raster.width,
raster.height=raster.height,
raster.dpi=raster.dpi,
...
)
)
}
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