R/krsa_cv_plot.R

In CogDisResLab/KRSA: KRSA: Kinome Random Sampling Analyzer

#' Generates CV (coefficient of variation) plot
#'
#' This function takes in the modeled pw data, list of peptides, and sample names (optional)
#'
#' @param data krsa modeled pw data (scaled)
#' @param peptides peptide list
#' @param samples sample names
#'
#' @return ggplot object
#'
#' @family plots
#'
#' @export
#'
#' @examples
#' TRUE
krsa_cv_plot <- function(data, peptides, samples = NULL) {
    data %>%
        dplyr::filter(Peptide %in% peptides) %>%
        {
            if (!is.null(samples)) dplyr::filter(., SampleName %in% samples) else .
        } %>%
        dplyr::group_by(Group, Peptide) %>%
        dplyr::summarise(SD = stats::sd(slope), repMean = mean(slope), CV = SD / repMean) %>%
        ggplot2::ggplot(ggplot2::aes(.data$repMean, .data$CV)) +
        ggplot2::geom_point() +
        ggplot2::geom_smooth(method = "loess", ggplot2::aes(color = Group)) +
        ggplot2::facet_wrap(~Group, scales = "free") +
        ggplot2::ylim(0, 1) +
        ggplot2::labs(title = "CV Plot") +
        ggplot2::theme_bw()
}