R/krsa_waterfall.R

In CogDisResLab/KRSA: KRSA: Kinome Random Sampling Analyzer

#' Generates a waterfall figure based on the LFC table
#'
#' Takes in the LFC table and a LFC cuttoff and generates a waterfall plot using a ggplot.
#'
#' @param data LFC table
#' @param lfc_thr LFC cutoff for plot
#' @param byChip boolean Select T if the LFC is based on a byChip analysis
#' @param sd_thr SD cutoff for plot
#'
#' @return ggplot object
#'
#' @family plots
#'
#'
#' @export
#'
#' @examples
#' TRUE
krsa_waterfall <- function(data, lfc_thr, byChip = T, sd_thr = Inf) {
    if (byChip == T) {
        data %>%
            dplyr::filter(LFC_SD <= sd_thr) -> data

        data$colMean <- cut(data$totalMeanLFC, breaks = c(-Inf, -1 * lfc_thr, lfc_thr, Inf), labels = c("red", "black", "red"))
        data$colFC <- cut(data$LFC, breaks = c(-Inf, -1 * lfc_thr, lfc_thr, Inf), labels = c("black", "gray", "black"))
    } else {
        data$colFC <- cut(data$LFC, breaks = c(-Inf, -1 * lfc_thr, lfc_thr, Inf), labels = c("red", "black", "red"))
    }

    ggplot2::ggplot(data) -> gg



    if (byChip == T) {
        gg <- gg +
            ggplot2::geom_point(ggplot2::aes(LFC, stats::reorder(Peptide, LFC)), color = data$colFC, size = 0.75) +
            ggplot2::geom_point(ggplot2::aes(totalMeanLFC, stats::reorder(Peptide, totalMeanLFC)), color = data$colMean, size = 2) +
            ggplot2::geom_line(ggplot2::aes(LFC, stats::reorder(Peptide, totalMeanLFC)), alpha = 1 / 3)
    } else {
        gg <- gg +
            ggplot2::geom_segment(ggplot2::aes(x = 0, xend = LFC, y = stats::reorder(Peptide, LFC), yend = stats::reorder(Peptide, LFC)), color = "grey") +
            ggplot2::geom_point(ggplot2::aes(LFC, stats::reorder(Peptide, LFC)), color = data$colFC, size = 2)
    }




    gg +
        ggplot2::geom_vline(xintercept = 0) +
        ggplot2::geom_vline(xintercept = -1 * lfc_thr, linetype = "dashed") +
        ggplot2::geom_vline(xintercept = lfc_thr, linetype = "dashed") +
        ggplot2::labs(
            x = "Log2 Fold Change",
            y = ""
        ) +
        ggplot2::theme(
            plot.title  = ggplot2::element_text(size = 7),
            axis.text.y = ggplot2::element_text(size = 5)
        ) +
        ggplot2::theme_bw()
}