R/heatmap.3.noddg.R

In TROM: Transcriptome Overlap Measure

heatmap.3.noddg <-
function (x, 
                       max_score = 6, 
                       Rowv = TRUE, 
                       Colv = if (symm) "Rowv" else TRUE, 
                       distfun = dist, 
                       hclustfun = hclust, 
                       dendrogram = c("both", "row", "column", "none"), 
                       symm = FALSE, 
                       scale = c("none", "row", "column"), 
                       na.rm = TRUE, 
                       revC = identical(Colv, "Rowv"), 
                       add.expr, 
                       breaks, 
                       symbreaks = min(x < 0, na.rm = TRUE) || scale != "none", col = "heat.colors", 
                       colsep, 
                       rowsep, 
                       sepcolor = "white", 
                       sepwidth = c(0.05, 0.05), 
                       cellnote, 
                       notecex = 1, 
                       notecol = "cyan", 
                       na.color = par("bg"), 
                       trace = c("column", "row", "both", "none"), 
                       tracecol = "cyan", 
                       hline = median(breaks), 
                       vline = median(breaks), 
                       linecol = tracecol, 
                       margins = c(5, 5), 
                       ColSideColors, 
                       RowSideColors, 
                       cexRow = 0.2 + 1/log10(nr), 
                       cexCol = 0.2 + 1/log10(nc), 
                       labRow = NULL, 
                       labCol = NULL, 
                       key = TRUE, 
                       keysize = 1.5, 
                       density.info = c("histogram", "density", "none"), 
                       denscol = tracecol, 
                       symkey = min(x < 0, na.rm = TRUE) || symbreaks, 
                       densadj = 0.25, 
                       main = NULL, 
                       xlab = NULL, 
                       ylab = NULL, 
                       lmat = NULL, 
                       lhei = NULL, 
                       lwid = NULL, 
                       leftMargin=7, 
                       bottomMargin=7, 
                       reverse=FALSE,
    ...) 
{
    x[x>=max_score] <- max_score
    maxx <- max(x)
    x <- maxx-x
    zlim<- range(x)
    scale01 <- function(x, low = min(x), high = max(x)) {
        x <- (x - low)/(high - low)
        x
    }
    retval <- list()
    scale <- if (symm && missing(scale)) 
        "none"
    else match.arg(scale)
    dendrogram <- match.arg(dendrogram)
    trace <- match.arg(trace)
    density.info <- match.arg(density.info)
    if (length(col) == 1 && is.character(col)) 
        col <- get(col, mode = "function")
    if (!missing(breaks) && (scale != "none")) 
        warning("Using scale=\"row\" or scale=\"column\" when breaks are", 
            "specified can produce unpredictable results.", "Please consider using only one or the other.")
    if (is.null(Rowv) || is.na(Rowv)) 
        Rowv <- FALSE
    if (is.null(Colv) || is.na(Colv)) 
        Colv <- FALSE
    else if (Colv == "Rowv" && !isTRUE(Rowv)) 
        Colv <- FALSE
    if (length(di <- dim(x)) != 2 || !is.numeric(x)) 
        stop("`x' must be a numeric matrix")
    nr <- di[1]
    nc <- di[2]
    if (nr <= 1 || nc <= 1) 
        stop("`x' must have at least 2 rows and 2 columns")
    if (!is.numeric(margins) || length(margins) != 2) 
        stop("`margins' must be a numeric vector of length 2")
    if (missing(cellnote)) 
        cellnote <- matrix("", ncol = ncol(x), nrow = nrow(x))
    if (!inherits(Rowv, "dendrogram")) {
        if (((!isTRUE(Rowv)) || (is.null(Rowv))) && (dendrogram %in% 
            c("both", "row"))) {
            if (is.logical(Colv) && (Colv)) 
                dendrogram <- "column"
            else dedrogram <- "none"
            warning("Discrepancy: Rowv is FALSE, while dendrogram is `", 
                dendrogram, "'. Omitting row dendogram.")
        }
    }
    if (!inherits(Colv, "dendrogram")) {
        if (((!isTRUE(Colv)) || (is.null(Colv))) && (dendrogram %in% 
            c("both", "column"))) {
            if (is.logical(Rowv) && (Rowv)) 
                dendrogram <- "row"
            else dendrogram <- "none"
            warning("Discrepancy: Colv is FALSE, while dendrogram is `", 
                dendrogram, "'. Omitting column dendogram.")
        }
    }
    if (inherits(Rowv, "dendrogram")) {
        ddr <- Rowv
        rowInd <- order.dendrogram(ddr)
    }
    else if (is.integer(Rowv)) {
        hcr <- hclustfun(distfun(x))
        ddr <- as.dendrogram(hcr)
        ddr <- reorder(ddr, Rowv)
        rowInd <- order.dendrogram(ddr)
        if (nr != length(rowInd)) 
            stop("row dendrogram ordering gave index of wrong length")
    }
    else if (isTRUE(Rowv)) {
        Rowv <- rowMeans(x, na.rm = na.rm)
        hcr <- hclustfun(distfun(x))
        ddr <- as.dendrogram(hcr)
        ddr <- reorder(ddr, Rowv)
        rowInd <- order.dendrogram(ddr)
        if (nr != length(rowInd)) 
            stop("row dendrogram ordering gave index of wrong length")
    }
    else {
        rowInd <- nr:1
    }
    if (inherits(Colv, "dendrogram")) {
        ddc <- Colv
        colInd <- order.dendrogram(ddc)
    }
    else if (identical(Colv, "Rowv")) {
        if (nr != nc) 
            stop("Colv = \"Rowv\" but nrow(x) != ncol(x)")
        if (exists("ddr")) {
            ddc <- ddr
            colInd <- order.dendrogram(ddc)
        }
        else colInd <- rowInd
    }
    else if (is.integer(Colv)) {
        hcc <- hclustfun(distfun(if (symm) 
            x
        else t(x)))
        ddc <- as.dendrogram(hcc)
        ddc <- reorder(ddc, Colv)
        colInd <- order.dendrogram(ddc)
        if (nc != length(colInd)) 
            stop("column dendrogram ordering gave index of wrong length")
    }
    else if (isTRUE(Colv)) {
        Colv <- colMeans(x, na.rm = na.rm)
        hcc <- hclustfun(distfun(if (symm) 
            x
        else t(x)))
        ddc <- as.dendrogram(hcc)
        ddc <- reorder(ddc, Colv)
        colInd <- order.dendrogram(ddc)
        if (nc != length(colInd)) 
            stop("column dendrogram ordering gave index of wrong length")
    }
    else {
        colInd <- 1:nc
    }
    retval$rowInd <- rowInd
    retval$colInd <- colInd
    retval$call <- match.call()
    x <- x[rowInd, colInd]
    x.unscaled <- x
    cellnote <- cellnote[rowInd, colInd]
    if (is.null(labRow)) 
        labRow <- if (is.null(rownames(x))) 
            (1:nr)[rowInd]
        else rownames(x)
    else labRow <- labRow[rowInd]
    if (is.null(labCol)) 
        labCol <- if (is.null(colnames(x))) 
            (1:nc)[colInd]
        else colnames(x)
    else labCol <- labCol[colInd]
    if (scale == "row") {
        retval$rowMeans <- rm <- rowMeans(x, na.rm = na.rm)
        x <- sweep(x, 1, rm)
        retval$rowSDs <- sx <- apply(x, 1, sd, na.rm = na.rm)
        x <- sweep(x, 1, sx, "/")
    }
    else if (scale == "column") {
        retval$colMeans <- rm <- colMeans(x, na.rm = na.rm)
        x <- sweep(x, 2, rm)
        retval$colSDs <- sx <- apply(x, 2, sd, na.rm = na.rm)
        x <- sweep(x, 2, sx, "/")
    }
    if (missing(breaks) || is.null(breaks) || length(breaks) < 
        1) {
        if (missing(col) || is.function(col)) 
            breaks <- 16
        else breaks <- length(col) + 1
    }

    if (length(breaks) == 1) {
        if (!symbreaks) 
            if (length(zlim)>0) {
				breaks <- seq(zlim[1], zlim[2], 
	                length = breaks)
			} else {
				breaks <- seq(min(x, na.rm = na.rm), max(x, na.rm = na.rm), 
	                length = breaks)
			}
        else {
            extreme <- max(abs(x), na.rm = TRUE)
            breaks <- seq(-extreme, extreme, length = breaks)
        }
    }
    nbr <- length(breaks)
    ncol <- length(breaks) - 1
    if (class(col) == "function") 
        col <- col(ncol)
    min.breaks <- min(breaks)
    max.breaks <- max(breaks)
    x[x < min.breaks] <- min.breaks
    x[x > max.breaks] <- max.breaks
    if (missing(lhei) || is.null(lhei)) 
        lhei <- c(keysize, 4)
    if (missing(lwid) || is.null(lwid)) 
        lwid <- c(keysize, 4)
    if (missing(lmat) || is.null(lmat)) {
        lmat <- rbind(4:3, 2:1)
        if (!missing(ColSideColors)) {
            if (!is.character(ColSideColors) || length(ColSideColors) != 
                nc) 
                stop("'ColSideColors' must be a character vector of length ncol(x)")
            lmat <- rbind(lmat[1, ] + 1, c(NA, 1), lmat[2, ] + 
                1)
            lhei <- c(lhei[1], 0.2, lhei[2])
        }
        if (!missing(RowSideColors)) {
            if (!is.character(RowSideColors) || length(RowSideColors) != 
                nr) 
                stop("'RowSideColors' must be a character vector of length nrow(x)")
            lmat <- cbind(lmat[, 1] + 1, c(rep(NA, nrow(lmat) - 
                1), 1), lmat[, 2] + 1)
            lwid <- c(lwid[1], 0.2, lwid[2])
        }
        lmat[is.na(lmat)] <- 0
    }
    if (length(lhei) != nrow(lmat)) 
        stop("lhei must have length = nrow(lmat) = ", nrow(lmat))
    if (length(lwid) != ncol(lmat)) 
        stop("lwid must have length = ncol(lmat) =", ncol(lmat))
    op <- par(no.readonly = TRUE)
    on.exit(par(op))
    #layout(lmat, widths = lwid, heights = lhei, respect = FALSE)
    layout(matrix(c(1,2), nrow=1), widths = c(9,1.3), respect = FALSE)
    if (!missing(RowSideColors)) {
        par(mar = c(margins[1], 0, 0, 0.5))
        image(rbind(1:nr), col = RowSideColors[rowInd], axes = FALSE)
    }
    if (!missing(ColSideColors)) {
        par(mar = c(0.5, 0, 0, margins[2]))
        image(cbind(1:nc), col = ColSideColors[colInd], axes = FALSE)
    }
    #par(mar = c(margins[1], margins[2]+2, 0, margins[2]))
    par(mar = c(bottomMargin, leftMargin, 4, 3), xpd=TRUE)
    x <- t(x)
    cellnote <- t(cellnote)
    if (revC) {
        iy <- nr:1
        if (exists("ddr")) 
            ddr <- rev(ddr)
        x <- x[, iy]
        cellnote <- cellnote[, iy]
    }
    else iy <- 1:nr
    if (!reverse) {
		image(1:nc, 1:nr, x[,ncol(x):1], xlim = 0.5 + c(0, nc), ylim = 0.5 + 
	        c(0, nr), axes = FALSE, xlab = "", ylab = "", col = col, 
	        #breaks = breaks, 
			zlim = if (length(zlim)>0) zlim else range(x), ...)
	} else {
		image(1:nc, 1:nr, x[nrow(x):1,ncol(x):1], xlim = 0.5 + c(0, nc), ylim = 0.5 + 
	        c(0, nr), axes = FALSE, xlab = "", ylab = "", col = col, 
	        #breaks = breaks, 
			zlim = if (length(zlim)>0) zlim else range(x), ...)
	}
    retval$carpet <- x
    if (exists("ddr")) 
        retval$rowDendrogram <- ddr
    if (exists("ddc")) 
        retval$colDendrogram <- ddc
    retval$breaks <- breaks
    retval$col <- col
    if (!invalid(na.color) & any(is.na(x))) {
        mmat <- ifelse(is.na(x), 1, NA)
        image(1:nc, 1:nr, mmat, axes = FALSE, xlab = "", ylab = "", 
            col = na.color, add = TRUE)
    }
    if (!is.null(xlab)) 
        #mtext(xlab, side = 1, line = margins[1] - 1.25)
        mtext(xlab, side = 1, line = 1)
    axis(2, 1:nr, labels = rev(labRow), las = 2, line = 0, tick = 1, 
        cex.axis = cexRow)
	axis(1, 1:nc, labels = labCol, las = 2, line = 0, tick = 1, 
        cex.axis = cexCol)
# 	if (length(axis3labels)>0) {
# 		axis(1, at=1:nc, labels = axis3labels, las = 2, line = 5, tick = 0, 
# 			cex.axis = cexCol)
# 	}
# 	if (length(axis4labels)>0) {
# 		axis(4, at=1:nr, labels = axis4labels, las = 2, line = 0, tick = 1, 
# 		        cex.axis = cexRow)
# 		mtext("# genes", side=4, line=0, at=c(nr+1.5, nr+1.5), las=2)
# 	}
	
	box()
    if (!is.null(ylab)) 
        mtext(ylab, side = 4, line = margins[2] - 1.25)
    if (!missing(add.expr)) 
        eval(substitute(add.expr))
    if (!missing(colsep)) 
        for (csep in colsep) rect(xleft = csep + 0.5, ybottom = rep(0, 
            length(csep)), xright = csep + 0.5 + sepwidth[1], 
            ytop = rep(ncol(x) + 1, csep), lty = 1, lwd = 1, 
            col = sepcolor, border = sepcolor)
    if (!missing(rowsep)) 
        for (rsep in rowsep) rect(xleft = 0, ybottom = (ncol(x) + 
            1 - rsep) - 0.5, xright = nrow(x) + 1, ytop = (ncol(x) + 
            1 - rsep) - 0.5 - sepwidth[2], lty = 1, lwd = 1, 
            col = sepcolor, border = sepcolor)
    min.scale <- min(breaks)
    max.scale <- max(breaks)
    x.scaled <- scale01(t(x), min.scale, max.scale)
    if (trace %in% c("both", "column")) {
        retval$vline <- vline
        vline.vals <- scale01(vline, min.scale, max.scale)
        for (i in colInd) {
            if (!is.null(vline)) {
                abline(v = i - 0.5 + vline.vals, col = linecol, 
                  lty = 2)
            }
            xv <- rep(i, nrow(x.scaled)) + x.scaled[, i] - 0.5
            xv <- c(xv[1], xv)
            yv <- 1:length(xv) - 0.5
            lines(x = xv, y = yv, lwd = 1, col = tracecol, type = "s")
        }
    }
    if (trace %in% c("both", "row")) {
        retval$hline <- hline
        hline.vals <- scale01(hline, min.scale, max.scale)
        for (i in rowInd) {
            if (!is.null(hline)) {
                abline(h = i + hline, col = linecol, lty = 2)
            }
            yv <- rep(i, ncol(x.scaled)) + x.scaled[i, ] - 0.5
            yv <- rev(c(yv[1], yv))
            xv <- length(yv):1 - 0.5
            lines(x = xv, y = yv, lwd = 1, col = tracecol, type = "s")
        }
    }

	#### add paths
# 	count <- 0 # count the number of marks ("x")
# 	if (!is.null(paths)) {
# 		for (i in 1:length(paths)) {
# 			path <- paths[[i]]
# 			if (!is.null(path.colors)) {
# 				lines(path, type="s", col=path.colors[i], lwd=4)
# 			} else {
# 				lines(path, type="s", col=2, lwd=4)
# 			}
			#lines(path, lty=2, col=2, lwd=2)
			#points(path, pch=4, col="blue", lwd=2)
			#points(path[which(path[,2] %in% fly_marks & !(path[,1] %in% excluded_worm_marks)),], pch=4, col="blue", lwd=2)
			#if (numbers) {
			#	for (r in which(path[,2] %in% fly_marks & !(path[,1] %in% excluded_worm_marks))) {
			#		count <- count + 1
			#		text(x=path[r,1], y=path[r,2]+1, labels=as.character(count), col="black")
# 				}
# 			}
# 		}
# 	}
	
	#### add horizontal and vertical lines #### 
# 	if (!is.null(horiz_lines)) {
# 		for (h in horiz_lines) {
# 			lines(x=c(0,nc+1), y=c(h,h), lwd=1.5)
# 		}
# 	}
# 	if (!is.null(vert_lines)) {
# 		for (v in vert_lines) {
# 			lines(x=c(v,v), y=c(0,nr+1), lwd=1.5)
# 		}
# 	}
# 	if (!is.null(blocks)) {
# 		for (i in 1:ncol(blocks)) {
# 			lines(x=blocks[c(1,3),i], y=blocks[c(2,4),i], type="s", col="blue", lwd=2)
# 			lines(x=blocks[c(1,3),i], y=blocks[c(2,4),i], type="S", col="blue", lwd=2)
# 		}
# 	}
# 	if (!is.null(marks)) {
# 		for (i in 1:ncol(marks)) {
# 			points(x=marks[1,i], y=marks[2,i], pch=4, col="blue", lwd=2)
# 		}
# 	}
# 	if (numbers) {
# 		for (i in 1:ncol(marks)) {
# 			text(x=marks[1,i], y=marks[2,i]+1, labels=as.character(count+i), col="black")
# 			#points(x=marks[1,i]+1, y=marks[2,i]+1, col="black")
# 		}
# 	}
	
# 	if (!is.null(similar_cell_marks)) {
# 		for (listInd in 1:(length(similar_cell_marks)-1)) {
# 			labels <- similar_cell_marks[[listInd]]
# 			wormInd <- sapply(labels[1,], FUN=function(x) {
# 				temp <- strsplit(x, "Worm")[[1]][2]
# 				which(labCol==temp)
# 			})
# 			flyInd <- sapply(labels[2,], FUN=function(x) {
# 				temp <- strsplit(x, "Fly")[[1]][2]
# 				which(rev(labRow)==temp)
# 			})
# 			text(x=wormInd, y=flyInd, labels=as.character(listInd), col=listInd)
# 		}
# 	}
# 	
	
	#####################
    if (!missing(cellnote)) 
        text(x = c(row(cellnote)), y = c(col(cellnote)), labels = c(cellnote), 
            col = notecol, cex = notecex)
    #par(mar = c(margins[1], 0, 0, 0))
    if (dendrogram %in% c("both", "row")) {
        plot(ddr, horiz = TRUE, axes = FALSE, yaxs = "i", leaflab = "none")
    }
    #else plot.new()
    #par(mar = c(0, 0, if (!is.null(main)) 5 else 0, margins[2]))
    if (dendrogram %in% c("both", "column")) {
        plot(ddc, axes = FALSE, xaxs = "i", leaflab = "none")
    }
    #else plot.new()
    if (!is.null(main)) 
        title(main, cex.main = 0.9 * op[["cex.main"]])
    if (key) {
        par(mar = c(7, 1, 4, 3), cex = 1)
        tmpbreaks <- breaks
        if (symkey) {
            max.raw <- max(abs(c(x, breaks)), na.rm = TRUE)
            min.raw <- -max.raw
            tmpbreaks[1] <- -max(abs(x), na.rm = TRUE)
            tmpbreaks[length(tmpbreaks)] <- max(abs(x), na.rm = TRUE)
        }
        else {
            if (length(zlim)>0) {
				min.raw <- zlim[1]
	            max.raw <- zlim[2]
			} else {
				min.raw <- min(x, na.rm = TRUE)
	            max.raw <- max(x, na.rm = TRUE)
			}
        }
		
        #z <- seq(min.raw, max.raw, length = length(col))
			  z <- seq(max.raw, min.raw, length = length(col))
        image(z = t(matrix(z, ncol = 1)), col = col, breaks = tmpbreaks, 
            xaxt = "n", yaxt = "n")
        par(usr = c(0, 1, 0, 1))
        lv <- as.numeric(pretty(breaks))
        xv <- scale01(lv, min.raw, max.raw)
		idx <- which(lv>=min.raw & lv<=max.raw)
#         if (!rescaling) {
# 			axis(4, at = xv, labels = lv, las=2)
# 		} else {
      axis(4, at = xv[idx], labels = lv[idx], las=2, cex.axis=0.8)
# 		}
        if (scale == "row") 
            mtext(side = 1, "Row Z-Score", line = 2)
        else if (scale == "column") 
            mtext(side = 1, "Column Z-Score", line = 2)
        #else mtext(side = 1, "Value", line = 2)
        else mtext(side = 1, "", line = 2)
        if (density.info == "density") {
            dens <- density(x, adjust = densadj, na.rm = TRUE)
            omit <- dens$x < min(breaks) | dens$x > max(breaks)
            dens$x <- dens$x[-omit]
            dens$y <- dens$y[-omit]
            dens$x <- scale01(dens$x, min.raw, max.raw)
            lines(dens$x, dens$y/max(dens$y) * 0.95, col = denscol, 
                lwd = 1)
            axis(2, at = pretty(dens$y)/max(dens$y) * 0.95, pretty(dens$y))
            title("Color Key\nand Density Plot")
            par(cex = 0.5)
            mtext(side = 2, "Density", line = 2)
        }
        else if (density.info == "histogram") {
            h <- hist(x, plot = FALSE, breaks = breaks)
            hx <- scale01(breaks, min.raw, max.raw)
            hy <- c(h$counts, h$counts[length(h$counts)])
            lines(hx, hy/max(hy) * 0.95, lwd = 1, type = "s", 
                col = denscol)
            axis(2, at = pretty(hy)/max(hy) * 0.95, pretty(hy))
            title("Color Key\nand Histogram")
            par(cex = 0.5)
            mtext(side = 2, "Count", line = 2)
        }
        #else title("Color Key")
    }
    else plot.new()
    retval$colorTable <- data.frame(low = retval$breaks[-length(retval$breaks)], 
        high = retval$breaks[-1], color = retval$col)
    invisible(retval)
}