R/pcaPlot.R

In Doscheda: A DownStream Chemo-Proteomics Analysis Pipeline

#' PCA of the main data sets contained in a object of class ChemoProtSet
#'
#'Plot of Principal Component Analysis for the first two principal components of the experimental data.
#'
#' @param x object of class 'ChemoProtSet'
#' @param ... other plot options
#'
#' @return PCA plot for objects of class ChemoProtSet
#' @seealso \code{\link{DoschedaSet}}
#' @export
#' @docType methods
#' @rdname pcaPlot-methods
#' @examples
#'ex <- processedExample
#'ex <- runNormalisation(ex)
#'ex <- fitModel(ex)
#'pcaPlot(ex)


setGeneric(name = "pcaPlot", def = function(x, ...) {
    standardGeneric("pcaPlot")
})

#' @rdname pcaPlot-methods
#' @import ggplot2
#' @importFrom stats prcomp
#' @aliases pcaPlot,ANY,ANY-method
#' @examples
#'ex <- processedExample
#'ex <- runNormalisation(ex)
#'ex <- fitModel(ex)
#'pcaPlot(ex)
#'
setMethod(f = "pcaPlot", signature = "ChemoProtSet", definition = function(x, ...) {
    if (x@parameters$dataType == "intensity") {
        
        nchan <- x@parameters$chans - 1
        
    } else {
        
        nchan <- x@parameters$chans
    }
    
    su <- x@finalData
    
    reps <- x@parameters$reps
    index <- 1:(nchan * reps)
    pca <- prcomp(su[, 1:length(index)], scale = FALSE)
    
    DTA <- data.frame(as.numeric(t(su[, 1:length(index)]) %*% pca$x[, 1]), as.numeric(t(su[, 1:length(index)]) %*% 
        pca$x[, 2]))
    
    p <- ggplot2::ggplot(DTA, ggplot2::aes(x = DTA$as.numeric.t.su...1.length.index........pca.x...1.., 
        y = DTA$as.numeric.t.su...1.length.index........pca.x...2..))
    
    paste0("PC1", " (", round(pca$sdev[1]/sum(pca$sdev) * 100, 0), "%)")
    
    shapeval <- c(15:18, 7:12)
    p <- p + ggplot2::geom_point(ggplot2::aes(colour = factor(rep(1:reps, each = (nchan)), labels = paste("Rep", 
        1:reps))[index], shape = factor(rep(1:nchan, reps), labels = c(paste("C", 0:(nchan - 1), 
        sep = "")))[index]), size = 5) + scale_shape_manual(values = shapeval[1:nchan]) + ggplot2::labs(x = paste0("PC1", 
        " (", round(pca$sdev[1]/sum(pca$sdev) * 100, 0), "%)"), y = paste0("PC2", " (", round(pca$sdev[2]/sum(pca$sdev) * 
        100, 0), "%)"), title = "PCA") + ggplot2::labs(color = "Replicates", shape = "Concentration")
    
    p
})