R/krsa_zscores_plot.R

In CogDisResLab/KRSA: KRSA: Kinome Random Sampling Analyzer

#' Generates a waterfall figure based on the Z score table
#'
#' Takes in the Z score table and generates a waterfall plot using a ggplot.
#'
#' @param Ztable Z score table
#'
#' @return ggplot object
#'
#' @family plots
#'
#'
#' @export
#'
#' @examples
#' TRUE
krsa_zscores_plot <- function(Ztable) {
    Ztable %>%
        dplyr::filter(!Kinase %in% c("VRK2", "BARK1")) %>%
        dplyr::mutate(
            breaks = cut(
                abs(AvgZ),
                breaks = c(0, 1, 1.5, 2, Inf),
                right = F,
                labels = c("Z <= 1", "1 >= Z < 1.5", "1.5 >= Z < 2", "Z >= 2")
            )
        ) %>%
        ggplot2::ggplot() +
        ggplot2::geom_line(ggplot2::aes(Z, stats::reorder(Kinase, AvgZ)), alpha = 1 / 3) +
        ggplot2::geom_point(ggplot2::aes(Z, stats::reorder(Kinase, AvgZ)), color = "grey", size = 1) +
        ggplot2::geom_point(ggplot2::aes(AvgZ, stats::reorder(Kinase, AvgZ), color = breaks), size = 2) +
        ggplot2::geom_vline(xintercept = 0) +
        ggplot2::geom_vline(xintercept = c(-1, -1.5, -2, 1, 1.5, 2), linetype = "dashed") +
        ggplot2::scale_color_brewer(palette = "Reds", drop = F, guide = ggplot2::guide_legend(reverse = TRUE, title = "")) +
        ggplot2::labs(
            x = "Z",
            y = "",
            shape = "cutoff"
        ) +
        ggplot2::theme(
            plot.title  = ggplot2::element_text(size = 7),
            axis.text.y = ggplot2::element_text(size = 6)
        ) +
        ggplot2::theme_bw()
}