R/plot_hexbin_fc.R

In schex: Hexbin plots for single cell omics data

#' Plot of fold change of selected gene in single cell data using 
#'    bivariate hexagon cells.
#'
#' @param sce A \code{\link[SingleCellExperiment]{SingleCellExperiment}}
#'    or \code{\link[Seurat]{Seurat-class}} object.
#' @param col A string referring to the name of one column in the meta data of
#'    sce by which to compare. Note this factor can only contain two levels.
#' @param mod A string referring to the name of one column in the meta data of
#'    sce by which to compare. Note this factor can only contain two levels.
#' @param type A string referring to the name of one column in the meta data of
#'    sce by which to compare. Note this factor can only contain two levels.
#' @param feature A string referring to the name of one feature.
#' @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 colors A vector of strings specifying which colors to use for plotting
#'    the different levels in the selected column of the meta data.
#'
#' @details This function plots fold change within each 
#'   hexagon, which are calculated with \code{\link{make_hexbin}}. 
#'   Note that the fold change is only accurate if the condition 
#'   investigated is within the same individual. For conditions across 
#'   different individuals different methods that account for 
#'   individual-specific effects are required.
#'   
#' @return A \code{\link{ggplot2}{ggplot}} object.
#' @import Seurat
#' @import SingleCellExperiment
#' @import ggplot2
#' @importFrom dplyr as_tibble
#' @export
#'
#' @examples
#' #' # For Seurat object
#' library(Seurat)
#' data("pbmc_small")
#' pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA")
#' pbmc_small$test <- as.factor(sample(1:2, dim(pbmc_small)[2], replace=TRUE))
#' plot_hexbin_fc(pbmc_small, col="test", 
#' feature="CA2", type="scale.data")

plot_hexbin_fc <- function(sce,
    col,
    mod="RNA",
    type,
    feature,
    title=NULL,
    xlab=NULL,
    ylab=NULL,
    colors){
  
    out <- .extract_hexbin(sce)
    cID <- .extract_cID(sce)
  
    if(is.null(out)){
        stop("Compute hexbin representation before plotting.")
    }
  
    x <- .prepare_data_meta(sce, col)
    x_gene <-.prepare_data_feature(sce, mod, type, feature)
  
    .plot_hexbin_fc_helper(x, x_gene, feature, out, cID, col, title, 
                         xlab, ylab, colors)
  
} 

.plot_hexbin_fc_helper <- function(x, x_gene, feature, out, cID, col, 
    title, xlab, ylab, colors) {
  
    hh <- .make_hexbin_fc_function(x, x_gene, cID)
    ind_null <- unlist(lapply(hh, is.null))
    hh[ind_null] <- NA
    hh <- unlist(hh)
    out <- as_tibble(out)
  
    if(grepl("^[[:digit:]]", feature )){
        feature <- paste0("G_", feature)
    }
  
    feature <- gsub("-", "_", feature)
  
    col_hh <- paste0(feature, "_", "fc")
  
    func1 <- paste0("out$", col_hh, " <- hh")
    eval(parse(text=func1))
  
    .plot_hexbin(out, colour_by=col_hh,
        title=title, xlab=xlab, ylab=ylab)
}