#' Plot of meta data of single cell data in bivariate hexagon cells.
#'
#' @param sce A \code{\link[SingleCellExperiment]{SingleCellExperiment}} object.
#' @param col A string referring to the name of one column in the meta data of
#' sce by which to colour the hexagons.
#' @param action A string specifying how meta data of observations in
#' binned hexagon cells are to be summarized. Possible actions are
#' \code{majority}, \code{prop}, \code{prop_0}, \code{mode}, \code{mean} and
#' \code{median} (see details).
#' @param no An integer specifying which level to plot of the column. Only in
#' effect when \code{action=prop}.
#' @param colors A vector of strings specifying which colors to use for plotting
#' the different levels in the selected column of the meta data. Only in
#' effect when the selected \code{action="majority"}.
#' @param title A string containing the title of the plot.
#' @param xlab A string containing the title of the x axis.
#' @param ylab A string containing the title of the y axis.
#' @param na.rm Logical indicating whether NA values should be removed.
#'
#' @details This function plots any column of the meta data in the hexagon cell
#' representation calculated with \code{\link{make_hexbin}}. The chosen meta
#' data column is summarized by one of six actions \code{majority},
#' \code{prop}, \code{prop_0}, \code{mode}, \code{mean} and \code{median}:
#'
#' \describe{
#' \item{\code{majority}}{Returns the value of the majority of
#' observations in the bin. The associated meta data column needs to be
#' a factor or character.}
#' \item{\code{prop}}{Returns the proportion of each level or unique
#' character in the bin. The associated meta data column needs to be
#' a factor or character}
#' \item{\code{prop_0}}{Returns the proportion of observations in the b
#' factor or character in the bin
#' greater than 0. The associated meta data column needs to be numeric.}
#' \item{\code{mode}}{Returns the mode of the observations in the bin. The
#' associated meta data column needs to be numeric.}
#' \item{\code{mean}}{Returns the mean of the observations in the bin. The
#' associated meta data column needs to be numeric.}
#' \item{\code{median}}{Returns the median of the observations in the bin.
#' The associated meta data column needs to be numeric.}
#' }
#'
#' @return A \code{\link{ggplot2}{ggplot}} object.
#' @import SingleCellExperiment
#' @import ggplot2
#' @importFrom dplyr as_tibble
#' @export
#'
#' @examples
#' # For SingleCellExperiment object
#' library(TENxPBMCData)
#' library(scater)
#' tenx_pbmc3k <- TENxPBMCData(dataset = "pbmc3k")
#' rm_ind <- calculateAverage(tenx_pbmc3k) < 0.1
#' tenx_pbmc3k <- tenx_pbmc3k[-rm_ind, ]
#' colData(tenx_pbmc3k) <- cbind(
#' colData(tenx_pbmc3k),
#' perCellQCMetrics(tenx_pbmc3k)
#' )
#' tenx_pbmc3k <- logNormCounts(tenx_pbmc3k)
#' tenx_pbmc3k <- runPCA(tenx_pbmc3k)
#' tenx_pbmc3k <- make_hexbin(tenx_pbmc3k, 20, dimension_reduction = "PCA")
#' plot_hexbin_meta(tenx_pbmc3k, col = "total", action = "median")
plot_hexbin_meta <- function(
sce,
col,
action,
no = 1,
colors = NULL,
title = NULL,
xlab = NULL,
ylab = NULL,
na.rm = FALSE) {
out <- .extract_hexbin(sce)
cID <- .extract_cID(sce)
x <- .prepare_data_meta(sce, col)
.plot_hexbin_meta_helper(
x, out, cID, col, action, no, title, xlab, ylab,
colors, na.rm
)
}
.plot_hexbin_meta_helper <- function(x, out, cID, col, action, no, title,
xlab, ylab, colors, na.rm) {
if (is.null(out)) {
stop("Compute hexbin representation before plotting.")
}
hh <- .make_hexbin_function(x, action, cID, na.rm, no)
out <- as_tibble(out)
if (action == "majority") {
if (is.factor(x)) {
out$meta <- factor(hh, levels = levels(x))
} else {
out$meta <- hh
}
} else {
out$meta <- hh
}
if (is.null(title)) {
if (action == "prop") {
title <- paste0(col, "_", action, "_", unique(x)[no])
} else {
title <- paste0(col, "_", action)
}
}
.plot_hexbin(out,
colour_by = "meta", action = action,
colors = colors, title = title, xlab = xlab, ylab = ylab
)
}
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