heatmap.3 <- function(x, 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 = max(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("none", "column","row", "both"), tracecol = "cyan", hline = median(breaks), vline = median(breaks), linecol = tracecol, margins = c(5,5), ColSideColors, RowSideColors, side.height.fraction=0.3, cexRow = 0.2 + 1/log10(nr), cexCol = 0.2 + 1/log10(nc), labRow = NULL, labCol = NULL, key = TRUE, keysize = 1.5, density.info = c("none", "histogram", "density"), denscol = tracecol, symkey = max(x < 0, na.rm = TRUE) || symbreaks, densadj = 0.25, main = NULL, xlab = NULL, ylab = NULL, lmat = NULL, lhei = NULL, lwid = NULL, ColSideColorsSize = 1, RowSideColorsSize = 1, KeyValueName="Value",...){ invalid <- function (x) { if (missing(x) || is.null(x) || length(x) == 0) return(TRUE) if (is.list(x)) return(all(sapply(x, invalid))) else if (is.vector(x)) return(all(is.na(x))) else return(FALSE) } x <- as.matrix(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) 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.matrix(ColSideColors)) #stop("'ColSideColors' must be a matrix") if (!is.character(ColSideColors) || nrow(ColSideColors) != nc) stop("'ColSideColors' must be a matrix of nrow(x) rows") lmat <- rbind(lmat[1, ] + 1, c(NA, 1), lmat[2, ] + 1) #lhei <- c(lhei[1], 0.2, lhei[2]) lhei=c(lhei[1], side.height.fraction*ColSideColorsSize/2, lhei[2]) } if (!missing(RowSideColors)) { #if (!is.matrix(RowSideColors)) #stop("'RowSideColors' must be a matrix") if (!is.character(RowSideColors) || ncol(RowSideColors) != nr) stop("'RowSideColors' must be a matrix of ncol(x) columns") lmat <- cbind(lmat[, 1] + 1, c(rep(NA, nrow(lmat) - 1), 1), lmat[,2] + 1) #lwid <- c(lwid[1], 0.2, lwid[2]) lwid <- c(lwid[1], side.height.fraction*RowSideColorsSize/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) if (!missing(RowSideColors)) { if (!is.matrix(RowSideColors)){ par(mar = c(margins[1], 0, 0, 0.5)) image(rbind(1:nr), col = RowSideColors[rowInd], axes = FALSE) } else { par(mar = c(margins[1], 0, 0, 0.5)) rsc = t(RowSideColors[,rowInd, drop=F]) rsc.colors = matrix() rsc.names = names(table(rsc)) rsc.i = 1 for (rsc.name in rsc.names) { rsc.colors[rsc.i] = rsc.name rsc[rsc == rsc.name] = rsc.i rsc.i = rsc.i + 1 } rsc = matrix(as.numeric(rsc), nrow = dim(rsc)[1]) image(t(rsc), col = as.vector(rsc.colors), axes = FALSE) if (length(rownames(RowSideColors)) > 0) { axis(1, 0:(dim(rsc)[2] - 1)/max(1,(dim(rsc)[2] - 1)), rownames(RowSideColors), las = 2, tick = FALSE) } } } if (!missing(ColSideColors)) { if (!is.matrix(ColSideColors)){ par(mar = c(0.5, 0, 0, margins[2])) image(cbind(1:nc), col = ColSideColors[colInd], axes = FALSE) } else { par(mar = c(0.5, 0, 0, margins[2])) csc = ColSideColors[colInd, , drop=F] csc.colors = matrix() csc.names = names(table(csc)) csc.i = 1 for (csc.name in csc.names) { csc.colors[csc.i] = csc.name csc[csc == csc.name] = csc.i csc.i = csc.i + 1 } csc = matrix(as.numeric(csc), nrow = dim(csc)[1]) image(csc, col = as.vector(csc.colors), axes = FALSE) if (length(colnames(ColSideColors)) > 0) { axis(2, 0:(dim(csc)[2] - 1)/max(1,(dim(csc)[2] - 1)), colnames(ColSideColors), las = 2, tick = FALSE) } } } par(mar = c(margins[1], 0, 0, margins[2])) 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 image(1:nc, 1:nr, x, xlim = 0.5 + c(0, nc), ylim = 0.5 + c(0, nr), axes = FALSE, xlab = "", ylab = "", col = col, breaks = breaks, ...) 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))) { # load library(gplots) mmat <- ifelse(is.na(x), 1, NA) image(1:nc, 1:nr, mmat, axes = FALSE, xlab = "", ylab = "", col = na.color, add = TRUE) } axis(1, 1:nc, labels = labCol, las = 2, line = -0.5, tick = 0, cex.axis = cexCol) if (!is.null(xlab)) mtext(xlab, side = 1, line = margins[1] - 1.25) axis(4, iy, labels = labRow, las = 2, line = -0.5, tick = 0, cex.axis = cexRow) 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") } } 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 = 1.5 * op[["cex.main"]]) if (key) { par(mar = c(5, 4, 2, 1), cex = 0.75) 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 { min.raw <- min(x, na.rm = TRUE) max.raw <- max(x, na.rm = TRUE) } z <- seq(min.raw, max.raw, length = length(col)) image(z = matrix(z, ncol = 1), col = col, breaks = tmpbreaks, xaxt = "n", yaxt = "n") par(usr = c(0, 1, 0, 1)) lv <- pretty(breaks) xv <- scale01(as.numeric(lv), min.raw, max.raw) axis(1, at = xv, labels = lv) 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, KeyValueName, 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) }