R/Plot_pca_score_stat.R

In statTarget: Statistical Analysis of Molecular Profiles

Plot_pca_score_stat <- function(pcx, pcy, scaling, Labels) {
    score = paste(getwd(), "/PCA_Data_", scaling, "/PCA_ScoreMatrix.csv", sep = "")
    ppppp = paste(getwd(), "/PCA_Data_", scaling, "/PCA_P", sep = "")
    Score <- read.csv(score, sep = ",", header = TRUE)
    Score.x <- Score[, 2:ncol(Score)]
    rownames(Score.x) <- Score[, 1]
    pwdK = paste(getwd(), "/scaleData_", scaling, "/class.csv", sep = "")
    k = read.csv(pwdK)
    slink = paste(getwd(), "/DataPretreatment", "/slink.csv", sep = "")
    slink = read.csv(slink, header = TRUE)
    Pvar <- read.csv(ppppp, sep = ",", header = TRUE)
    Pvar.x <- Pvar[, 2:ncol(Pvar)]
    rownames(Pvar.x) <- Pvar[, 1]
    pca <- paste("PC", pcx, " (", Pvar[pcx, 2], ") %")
    pcb <- paste("PC", pcy, " (", Pvar[pcy, 2], ")%")
    cum = Pvar[pcx, 2] + Pvar[pcy, 2]
    xlab = c(pca)
    ylab = c(pcb)
    lim = c()
    max.pc1 = 1.3 * (max(abs(Score.x[, pcx])))
    max.pc2 = 1.3 * (max(abs(Score.x[, pcy])))
    if (max.pc1 > max.pc2) {
        lim = c(-max.pc1, max.pc1)
    } else {
        lim = c(-max.pc2, max.pc2)
    }
    
    
    Epaxis <- dataEllipse_sT(Score.x[, pcx], Score.x[, pcy], levels = c(0.95), add = FALSE, draw = FALSE, 
        col = "black", lwd = 0.4, plot.points = FALSE, center.cex = 0.2)
    
    if (1.1 * max(Epaxis[, "x"]) < max(lim) & 1.1 * max(Epaxis[, "y"]) < max(lim)) {
        lim = lim
    } else {
        lim = c(1.2 * min(as.numeric(Epaxis)), 1.2 * max(as.numeric(Epaxis)))
    }
    
    
    
    tutticolors = matrix(c(1, 2, 3, 4, 5, 6, 7, 8, "rosybrown4", "green4", "navy", "purple2", "orange", 
        "pink", "chocolate2", "coral3", "khaki3", "thistle", "turquoise3", "palegreen1", "moccasin", 
        "olivedrab3", "azure4", "gold3", "deeppink"), ncol = 1)
    col = c()
    for (i in 1:nrow(k)) {
        col = c(col, tutticolors[k[i, 2], ])
    }
    D <- paste(getwd(), "/PCA_Data_", scaling, "/ScorePlot_PC", pcx, "vsPC", pcy, ".pdf", sep = "")
    pdf(D)
    # dev.new()
    graphics::plot(Score.x[, pcx], Score.x[, pcy], col = col, xlab = xlab, ylab = ylab, xlim = lim, 
        ylim = lim, pch = 19, sub = paste("Cumulative Proportion of Variance Explained = ", cum, "%", 
            sep = ""), main = paste("PCA Score Plot (", scaling, ")", sep = ""))
    axis(1, at = lim * 2, pos = c(0, 0), labels = FALSE, col = "grey", lwd = 0.7)
    axis(2, at = lim * 2, pos = c(0, 0), labels = FALSE, col = "grey", lwd = 0.7)
    # requireNamespace(car) library(car)
    dataEllipse_sT(Score.x[, pcx], Score.x[, pcy], levels = c(0.95), add = TRUE, col = "grey48", lwd = 0.4, 
        plot.points = FALSE, center.cex = 0.2)
    
    if (Labels) {
        text(Score.x[, pcx], Score.x[, pcy], col = col, cex = 0.5, labels = rownames(Score.x), pos = 1)
    } else {
        legend("topright", legend = levels(factor(slink[, 1])), bty = "n", pch = 19, col = seq_along(levels(factor(slink[, 
            1]))), text.col = seq_along(levels(factor(slink[, 1]))))
    }
    # dev.copy2pdf(file=D)
    dev.off()
}