R/PlotGroups.R

In maSigPro: Significant Gene Expression Profile Differences in Time Course Gene Expression Data

"PlotGroups" <- 
function (data, edesign = NULL, time = edesign[, 1], groups = edesign[, 
    c(3:ncol(edesign))], repvect = edesign[, 2], show.fit = FALSE, 
    dis = NULL, step.method = "backward", min.obs = 2, alfa = 0.05, nvar.correction = FALSE,
    summary.mode = "median", show.lines = TRUE, groups.vector = NULL, 
    xlab = "Time", ylab = "Expression value", cex.xaxis = 1, ylim = NULL, main = NULL, cexlab = 0.8, 
    legend = TRUE, sub = NULL, item = NULL ) 
{
    if (!is.vector(data)) {
        if (summary.mode == "representative") {
            distances <- apply(as.matrix(dist(data, diag = TRUE, 
                upper = TRUE)), 1, sum)
            representative <- names(distances)[distances == min(distances)]
            yy <- as.numeric(data[rownames(data) == representative, 
                ])
            sub <- paste("Representative:", representative)
        }
        else if (summary.mode == "median") {
            yy <- apply(as.matrix(data), 2, median, na.rm = TRUE)
if(is.null(sub)){
            sub <- paste("Median profile of", nrow(data), item, sep=" ")}
        }
        else stop("not valid summary.mode")
        if (dim(data)[1] == 1) {
            sub <- rownames(data)
        }
    }
    else if (length(data) != 0) {
        yy <- as.numeric(data)
        sub <- rownames(data)
        }
    else stop("empty data")
    if (is.null(ncol(groups))) {
        ncol = 1
        legend = FALSE
        codeg = "group"
    }
    else {
        ncol = ncol(groups)
        codeg <- as.character(colnames(groups))
    }
    reps <- i.rank(repvect)
    y <- vector(mode = "numeric", length = length(unique(reps)))
    x <- vector(mode = "numeric", length = length(unique(reps)))
    g <- matrix(nrow = length(unique(reps)), ncol = ncol)
    for (k in 1:length(y)) {
        y[k] <- mean(yy[reps == k], na.rm = TRUE)
        x[k] <- mean(time[reps == k])
        for (j in 1:ncol) {
            g[k, j] <- mean(groups[reps == k, j])
        }
    }
    if (is.null(ylim)) 
        ylim = c(min(as.numeric(yy), na.rm = TRUE), max(as.numeric(yy), 
            na.rm = TRUE))
    abcissa <- x
    xlim = c(min(abcissa, na.rm = TRUE), max(abcissa, na.rm = TRUE) * 
        1.3)
    color1 <- as.numeric(sort(factor(colnames(groups)))) + 1
    color2 <- groups
    for (j in 1:ncol) {
        color2[, j] <- color2[, j] * j
    }
    color2 <- as.vector(apply(color2, 1, sum) + 1)
    plot(x = time, y = yy, pch = 21, xlab = xlab, ylab = ylab, 
        xaxt = "n", main = main, sub = sub, ylim = ylim, xlim = xlim, 
        cex = cexlab, col = color2)
    axis(1, at = unique(abcissa), labels = unique(abcissa), cex.axis = cex.xaxis)
    if (show.fit) {
        rm <- matrix(yy, nrow = 1, ncol = length(yy))
        rownames(rm) <- c("ratio medio")
        colnames(rm) <- rownames(dis)
        fit.y <- T.fit(rm, design = dis, step.method = step.method, 
            min.obs = min.obs, alfa = alfa, nvar.correction = nvar.correction)
        betas <- fit.y$coefficients
    }
    for (i in 1:ncol(groups)) {
        group <- g[, i]
        if ((show.fit) && !is.null(betas)) {
            li <- c(2:6)
            a <- reg.coeffs(coefficients = betas, groups.vector =groups.vector, 
                group = colnames(groups)[i])
            a <- c(a, rep(0, (7 - length(a))))
            curve(a[1] + a[2] * x + a[3] * (x^2) + a[4] * (x^3) + 
                a[5] * (x^4) + a[6] * (x^5) + a[7] * (x^5), from = min(time), to = max(time), 
                col = color1[i], add = TRUE, lty = li[i])
        }
        if (show.lines) {
            lx <- abcissa[group != 0]
            ly <- y[group != 0]
            ord <- order(lx)
            lxo <- lx[ord]
            lyo <- ly[ord]
            lines(lxo, lyo, col = color1[i])
        }
    }
    op <- par(bg = "white")
    if (legend) 
        legend(max(abcissa, na.rm = TRUE) * 1.02, ylim[1], legend = codeg, 
            text.col = color1, col = color1, cex = cexlab, lty = 1, 
            yjust = 0)
    par(op)
}