R/krsa_curve_plot.R

In CogDisResLab/KRSA: KRSA: Kinome Random Sampling Analyzer

#' Generates curves plots per peptide using the last cycle data
#'
#' This function takes in the PW data (that includes all exposure times), list of peptides, and optional arguments of samples or groups names vector
#'
#' @param data PW data (that includes all exposure times)
#' @param peptides a vector of peptides to plot
#' @param byGroup fit lines by group
#' @param samples (optional) sample names
#' @param groups (optional) group names
#'
#' @return ggplot object
#'
#' @family plots
#'
#'
#' @export
#'
#' @examples
#' TRUE
krsa_curve_plot <- function(data, peptides, byGroup = T, samples = NULL, groups = NULL) {
    data %>%
        dplyr::filter(Peptide %in% peptides) %>%
        {
            if (!is.null(samples)) dplyr::filter(., SampleName %in% samples) else .
        } %>%
        {
            if (!is.null(groups)) dplyr::filter(., Group %in% groups) else .
        } %>%
        ggplot2::ggplot(ggplot2::aes(ExposureTime, Signal)) -> gg

    if (byGroup) {
        gg <- gg + ggplot2::geom_smooth(method = stats::lm, formula = y ~ x + 0, se = F, ggplot2::aes(color = factor(Group)))
    } else {
        gg <- gg + ggplot2::geom_smooth(method = stats::lm, formula = y ~ x + 0, se = F, ggplot2::aes(group = SampleName, color = factor(Group)))
    }

    gg +
        ggplot2::facet_wrap(~Peptide, scales = "free") +
        ggplot2::labs(title = paste0("Linear Model Fit of Signal Intensity Relative to Exposure Time at Post-wash Cycle of")) +
        ggplot2::theme_bw()
}