R/scatter_plot.R

In d93espinoza/barcodetrackR: Functions for Analyzing Cellular Barcoding Data

#' Scatter Plot
#'
#' Plots a scatter plot of two samples in the Summarized Experiment object
#'
#' @param your_SE A Summarized Experiment object of two samples.
#' @param assay The choice of assay to plot on the scatter plot. Set to "proportions" by default.
#' @param plot_labels The labels for the X and Y axis of the plot
#' @param method_corr Character. One of "pearson", "spearman", or "kendall". Can also use "manhattan" to compute manhattan distance instead.
#' @param display_corr Logical. Whether to display the computer correlation or not.
#' @param point_size Numeric. The size of the points being plotted.
#' @param your_title Logical. The title for the plot.
#' @param text_size Numeric. Size of text in plot.
#'
#' @return Displays a scatter plot of the specified assay for the specified samples in your_SE with correlation value optionally displayed.
#'
#' @importFrom rlang %||%
#' @importFrom magrittr %>%
#'
#' @export
#'
#' @examples
#' data(wu_subset)
#' scatter_plot(your_SE = wu_subset[, c(4, 8)])
#' # "
scatter_plot <- function(your_SE,
    assay = "proportions",
    plot_labels = colnames(your_SE),
    method_corr = "pearson",
    display_corr = TRUE,
    point_size = 0.5,
    your_title = "",
    text_size = 12) {

    # extracts assay from your_SE
    if (assay %in% names(SummarizedExperiment::assays(your_SE)) == FALSE) {
        stop("The specified assay is not found in your_SE.")
    }

    plotting_data <- SummarizedExperiment::assays(your_SE)[[assay]]


    if (ncol(plotting_data) != 2) {
        stop("your_SE must only contain 2 samples (columns)")
    }


    colnames(plotting_data) <- plot_labels

    plotting_data <- plotting_data[rowSums(plotting_data) > 0, ]
    if (display_corr) {
        if (method_corr == "manhattan") {
            correlation_label <- paste0(method_corr, " dist: ", round(cor.test(plotting_data[[1]], plotting_data[[2]], method = method_corr)$estimate, 3))
        } else {
            correlation_label <- paste0(method_corr, " corr: ", round(cor.test(plotting_data[[1]], plotting_data[[2]], method = method_corr)$estimate, 3))
        }
    } else {
        correlation_label <- NULL
    }

    gg_scatter <- ggplot2::ggplot(plotting_data, ggplot2::aes_(
        x = as.name(colnames(plotting_data)[1]),
        y = as.name(colnames(plotting_data)[2])
    )) +
        ggplot2::geom_point(size = point_size, color = "black") +
        ggplot2::theme(panel.background = ggplot2::element_rect(color = "black", fill = "white"), panel.grid = ggplot2::element_blank()) +
        ggplot2::xlab(plot_labels[1]) +
        ggplot2::ylab(plot_labels[2]) +
        ggplot2::ggtitle(paste0(your_title, "\n", correlation_label)) +
        ggplot2::theme(text = ggplot2::element_text(size = text_size))

    gg_scatter
}