R/generateBoxplot.R

In acc-bioinfo/TMBleR: Tumor Mutational Burden Quantification From Gene Panels And WES

#' Generate boxplots of TMB distribution versus clinical response
#'
#' This function generates boxplots representing the distribution of TMB
#' values between immunotherapy responders and nonresponders.
#' 
#' @param TMB_clinical dataframe generated by annotateTMB()
#' 
#' @return boxplot
#' @export
#' @examples 
#' #' # Import datasets
#' data(TMB_VanAllen)
#' data("VanAllen_Clinical")
#' # Annotate TMB with clinical reponse
#' TMB_clincal_response <- annotateTMB(TMB_df = TMB_VanAllen, ClinicalData = VanAllen_Clinical )
#' 
#' # generate plot
#' generateBoxplot(TMB_clincal_response)
generateBoxplot <- function(TMB_clinical){
 
    # sanity check
    if (nrow(TMB_clinical) == 0) stop("TMB_clinical should have at least one row")
    if (!methods::is(TMB_clinical, "data.frame")) stop("ClinicalData should be a data.frame")
    if (!any(colnames(TMB_clinical) %in% "ClinicalResponse")) stop("TMB_clinical did not have a column named ClinicalResponse")
    if (!any(colnames(TMB_clinical) %in% "Sample")) stop("TMB_clinical did not have a column named TMB_per_Mb")
    if (!any(colnames(TMB_clinical) %in% "Sample")) stop("TMB_clinical did not have a column named Filter")
    if (!any(colnames(TMB_clinical) %in% "Sample")) stop("TMB_clinical did not have a column named Panel")
    
    ggplot2::ggplot(TMB_clinical, ggplot2::aes(x = .data$ClinicalResponse, y = .data$TMB_per_Mb)) + 
        ggplot2::geom_boxplot(ggplot2::aes(fill = .data$ClinicalResponse)) + 
        ggplot2::facet_grid(.data$Filter ~ .data$Design) +
        ggplot2::ggtitle("compare TMB distribution from responders and non-responders")
    
}