R/heatmap.R

In AllenInstitute/scrattch.hicat: Hierarchical Iterative Clustering Analysis for Transcriptomic data

# Built on gplots::heatmap.2

#' A modified version of heatmap.2 from the gplots package for cluster plotting
#' 
#' @param x numeric matrix of the values to be plotted. 
#' @param Rowv determines if and how the \emph{row} dendrogram should be
#'   reordered.  By default, it is TRUE, which implies dendrogram is
#'   computed and reordered based on row means. If NULL or FALSE, then no
#'   dendrogram is computed and no reordering is done. If a
#'   \code{\link{dendrogram}}, then it is used "as-is", ie
#'   without any reordering. If a vector of integers, then dendrogram is
#'   computed and reordered based on the order of the vector.
#' @param Colv determines if and how the \emph{column} dendrogram should
#'   be reordered. Has the options as the \code{Rowv} argument above and
#'   \emph{additionally} when \code{x} is a square matrix,
#'   \code{Colv="Rowv"} means that columns should be treated identically
#'   to the rows.
#' @param distfun function used to compute the distance (dissimilarity)
#'   between both rows and columns.  Defaults to \code{\link{dist}}.
#' @param hclustfun function used to compute the hierarchical clustering
#'   when \code{Rowv} or \code{Colv} are not dendrograms.  Defaults to
#'   \code{\link{hclust}}.
#' @param dendrogram character string indicating whether to draw 'none',
#'   'row', 'column' or 'both' dendrograms.  Defaults to 'both'. However,
#'   if Rowv (or Colv) is FALSE or NULL and dendrogram is 'both', then a
#'   warning is issued and Rowv (or Colv) arguments are honoured.
#' @param reorderfun \code{function(d, w)} of dendrogram and weights for
#'   reordering the row and column dendrograms.  The default uses
#'   \code{\link{stats reorder.dendrogram}}.
#' @param symm logical indicating if \code{x} should be treated
#'   \bold{symm}etrically; can only be true when \code{x} is a
#'   square matrix.
#' @param scale character indicating if the values should be centered and
#'   scaled in either the row direction or the column direction, or
#'   none.  The default is \code{"none"}.
#' @param na.rm logical indicating whether \code{NA}'s should be removed.
#' @param revC logical indicating if the column order should be
#'   \code{\link{rev}}ersed for plotting, such that e.g., for the
#'   symmetric case, the symmetry axis is as usual.
#' @param add.expr expression that will be evaluated after the call to
#'   \code{image}.  Can be used to add components to the plot.
#' @param breaks (optional) Either a numeric vector indicating the
#'   splitting points for binning \code{x} into colors, or a integer
#'   number of break points to be used, in which case the break points
#'   will be spaced equally between \code{min(x)} and \code{max(x)}.
#' @param symbreaks Boolean indicating whether breaks should be
#'   made symmetric about 0. Defaults to \code{TRUE} if the data includes
#'   negative values, and to \code{FALSE} otherwise.
#' @param col colors used for the image. Defaults to heat colors
#'   (\code{heat.colors}).
#' @param colsep,rowsep,sepcolor (optional) vector of integers
#'   indicating which columns or rows should be separated from the
#'   preceding columns or rows by a narrow space of color
#'   \code{sepcolor}.
#' @param sepwidth (optional) Vector of length 2 giving the width
#'   (colsep) or height (rowsep) the separator box drawn by colsep and
#'   rowsep as a function of the width (colsep) or height (rowsep) of a
#'   cell. Defaults to \code{c(0.05, 0.05)}
#' @param cellnote (optional) matrix of character strings which will be
#'   placed within each color cell, e.g. p-value symbols.
#' @param notecex (optional) numeric scaling factor for \code{cellnote}
#'   items.
#' @param notecol (optional) character string specifying the color for
#'   \code{cellnote} text.  Defaults to "cyan".
#' @param na.color Color to use for missing value (\code{NA}). Defaults
#'   to the plot background color.
#' @param trace character string indicating whether a solid "trace" line
#'   should be drawn across 'row's or down 'column's, 'both' or 'none'.
#'   The distance of the line from the center of each color-cell is
#'   proportional to the size of the measurement. Defaults to 'column'.
#' @param tracecol character string giving the color for "trace"
#'   line. Defaults to "cyan".
#' @param hline,vline,linecol Vector of values within cells where a
#'   horizontal or vertical dotted line should be drawn.  The color of
#'   the line is controlled by \code{linecol}.  Horizontal  lines are only
#'   plotted if \code{trace} is 'row' or 'both'.  Vertical lines are only
#'   drawn if \code{trace} 'column' or 'both'.   \code{hline} and
#'   \code{vline} default to the median of the breaks, \code{linecol}
#'   defaults to the value of \code{tracecol}.
#' @param margins numeric vector of length 2 containing the margins
#'   (see \code{\link{par}(mar= *)}) for column and row names,
#'   respectively.
#' @param ColSideColors (optional) character vector of length
#'   \code{ncol(x)} containing the color names for a horizontal side bar
#'   that may be used to annotate the columns of \code{x}.
#' @param RowSideColors (optional) character vector of length
#'   \code{nrow(x)} containing the color names for a vertical side bar
#'   that may be used to annotate the rows of \code{x}.
#' @param cexRow,cexCol positive numbers, used as \code{cex.axis} in
#'   for the row or column axis labeling.  The defaults currently only
#'   use number of rows or columns, respectively.
#' @param labRow,labCol character vectors with row and column labels to
#'   use; these default to \code{rownames(x)} or \code{colnames(x)},
#'   respectively.
#' @param srtRow,srtCol angle of row/column labels, in degrees from
#'   horizontal
#' @param adjRow,adjCol 2-element vector giving the (left-right,
#'   top-bottom) justification of row/column labels (relative to the text
#'   orientation).
#' @param offsetRow,offsetCol Number of character-width spaces to
#'   place between row/column labels and the edge of the plotting
#'   region.
#' @param colRow,colCol color of row/column labels, either a scalar to
#'   set the color of all labels the same, or a vector providing the
#'   colors of each label item
#' @param keysize numeric value indicating the size of the key
#' @param density.info character string indicating whether to superimpose
#'   a 'histogram', a 'density' plot, or no plot ('none') on the
#'   color-key.
#' @param denscol character string giving the color for the density
#'   display specified by \code{density.info}, defaults to the same value
#'   as \code{tracecol}.
#' @param symkey Boolean indicating whether the color key should be
#'   made symmetric about 0. Defaults to \code{TRUE} if the data includes
#'   negative values, and to \code{FALSE} otherwise.
#' @param densadj Numeric scaling value for tuning the kernel width when
#'   a density plot is drawn on the color key.  (See the \code{adjust}
#'   parameter for the \code{density} function for details.)  Defaults to
#'   0.25.
#' @param key.title main title of the color key. If set to NA no title
#'   will be plotted.
#' @param key.xlab x axis label of the color key. If set to NA no label
#'   will be plotted.
#' @param key.ylab y axis label of the color key. If set to NA no label
#'   will be plotted.
#' @param key.xtickfun function computing tick location and labels for
#'   the xaxis of the color key. Returns a named list containing
#'   parameters that can be passed to \code{axis}. See examples.
#' @param key.ytickfun function computing tick location and labels for
#'   the y axis of the color key. Returns a named list containing
#'   parameters that can be passed to \code{axis}.  See examples.
#' @param key.par graphical parameters for the color key. Named list that
#'   can be passed to \code{par}.
#' @param main,xlab,ylab main, x- and y-axis titles; defaults to none.
#' @param lmat,lhei,lwid visual layout: position matrix, column height,
#'   column width.  See \code{\link{gplots::heatmap.2}} for details
#' @param extrafun A function to be called after all other work. See
#'   code{\link{gplots::heatmap.2}}.
#' @param ... additional arguments passed on to \code{\link{image}}
#' 
#' 
#' @return a base R plot
#' @export
#' 
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 = 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, 
                       ...) {
  
  scale01 <- function(x, 
                      low = min(x), 
                      high = max(x)) {
    x <- (x - low)/(high - low)
    x
  }
  
  # List for returned values
  retval <- list()
  
  # Argument matching
  scale <- if(symm && missing(scale)) {
    "none"
  } else {
    match.arg(scale)
  }
  
  dendrogram <- if(missing(dendrogram)) {
    "both"
  } else {
    match.arg(dendrogram)
  }
  
  trace <- if(missing(trace)) {
    "both"
  } else {
    match.arg(trace)
  }
  
  density.info <- if(missing(density.info)) {
    "none"
  } else {
    match.arg(density.info)
  }
  
  # convert col to a function call
  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")
  }
  
  # Get number of rows and columns from dims
  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")
  }
  # generate a blank cellnote matrix if not provided
  # not sure why you'd do this - why not just skip drawing the cellnote?
  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"))) {
      dendrogram <- ifelse(is.logical(Colv) && (Colv),
                           "column",
                           "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"))) {
      dendrogram <- ifelse(is.logical(Rowv) && (Rowv),
                           "row",
                           "none") 
      warning("Discrepancy: Colv is FALSE, while dendrogram is `", 
              dendrogram, "'. Omitting column dendogram.")
    }
  }
  
  # hierarchical clustering and dendrogram generation for rows
  if (inherits(Rowv, "dendrogram")) {
    # user-supplied row dendrogram
    ddr <- Rowv
    rowInd <- order.dendrogram(ddr)
  } else if (is.integer(Rowv)) {
    # computation for row dendrogram with provided order
    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)) {
    # computation for row dendrogram using row means for order
    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 {
    # use row indices if no dendrogram is required.
    # nr:1 because low values are at the bottom.
    rowInd <- nr:1
  }
  
  # hierarchical clustering and dendrogram generation for columns
  if (inherits(Colv, "dendrogram")) {
    # user-supplied col dendrogram
    ddc <- Colv
    colInd <- order.dendrogram(ddc)
  } else if (identical(Colv, "Rowv")) {
    # use the row dendrogram and order if rows and cols are mattched
    # e.g. for a symmetrical matrix
    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)) {
    # computation for col dendrogram with provided order
    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)) {
    # computation for row dendrogram using col means for order
    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 {
    # use row indices if no dendrogram is required.
    colInd <- 1:nc
  }
  
  # if hierarchical clustering was perfromed,
  # add the results to the return values
  if (exists("hcc")) {
    retval$hcc <- hcc
  }
  if (exists("hcr")) {
    retval$hcr <- hcr
  }
  
  # adding row and column indices to the return values
  retval$rowInd <- rowInd
  retval$colInd <- colInd
  retval$call <- match.call()
  
  # Re-sort the matrix based on row and column indices
  x <- x[rowInd, colInd]
  x.unscaled <- x
  # Re-sort the cell labels based on row and column indices
  cellnote <- cellnote[rowInd, colInd]
  
  # Generate row label vector
  if (is.null(labRow)) {
    if(is.null(rownames(x))) {
      labRow <- (1:nr)[rowInd]
    } else {
      labRow <- rownames(x)
    }
  } else {
    labRow <- labRow[rowInd]
  }
  
  # Generate col label vector
  if (is.null(labCol)) {
    if(is.null(colnames(x))) {
      labCol <- (1:nc)[colInd]
    } else {
      labCol <- colnames(x)
    }
  } else {
    labCol <- labCol[colInd]
  }
  
  # rescaling
  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, "/")
  }
  
  # generate value breaks for color palette
  if (missing(breaks) || is.null(breaks) || length(breaks) < 1) {
    breaks <- ifelse(missing(col) || is.function(col),
                     16,
                     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)
    }
  }
  
  # generate heatmap colors based on the number of 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)) { #|| ncol(ColSideColors) != nc) 
        stop("'ColSideColors' must be a character ") #vector of length ncol(x)")
      }
      lmat <- rbind(lmat[1, ] + 1, c(NA, 1), lmat[2, ] + 1)
      nnn <- ifelse(is.vector(ColSideColors),
                    1,
                    nrow(colSideColors))
      lhei <- c(lhei[1], nnn * 0.1, lhei[2])
    }
    if (!missing(RowSideColors)) {
      if (!is.character(RowSideColors)) { #|| length(RowSideColors) != nr) 
        stop("'RowSideColors' must be a character ")
      }
      nnn <- ifelse(is.vector(RowSideColors),
                    1,
                    ncol(RowSideColors))
      lmat <- cbind(lmat[, 1] + 1, 
                    c(rep(NA, nrow(lmat) - 1), 1), 
                    lmat[, 2] + 1)
      lwid <- c(lwid[1], nnn*0.1, 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)) {
    par(mar = c(margins[1], 0, 0, 0.5))
    
    if (is.vector(RowSideColors)) {
      image(rbind(1:nr), 
            col = RowSideColors[rowInd], 
            axes = FALSE)
    } 
    if (is.matrix(RowSideColors)) {
      jk.row <- RowSideColors
      jk.xy <- matrix(which(jk.row != "0"), dim(jk.row))
      colnames(jk.xy) <- colnames(jk.row)
      # image(t(jk.xy), col = jk.row[rowInd, ], xaxt="n", yaxt="n")
      # grid(nx=ncol(jk.row), ny=nrow(jk.row), lty=1, col="black")
      image(x = t(jk.xy), 
            col = jk.row[rowInd, ], 
            xaxt = "n", 
            yaxt = "n")
      # axis(3, at=seq(0,1,1/(ncol(jk.xy)-1)),labels=colnames(jk.xy), las=2, cex.axis = cexCol, tick=0)
      axis(side = 1, 
           at = seq(0, 1, 1 / (ncol(jk.xy) - 1)),
           labels = colnames(jk.xy), 
           las = 2, 
           cex.axis = cexCol, 
           tick = 0)
      # grid(nx=ncol(jk.row), ny=nrow(jk.row), lty=1, col="black")
    }
    
  }
  if (!missing(ColSideColors)) {
    par(mar = c(0.5, 0, 0, margins[2]))
    if (is.vector(ColSideColors)) {
      image(x = cbind(1:nc), 
            col = ColSideColors[colInd], 
            axes = FALSE)
    } 
    if (is.matrix(ColSideColors)) {
      jk.col <- ColSideColors
      jk.xy <- matrix(which(jk.col != "0"), dim(jk.col))
      image(x = t(jk.xy), 
            col = jk.col[, colInd], 
            axes = FALSE)
    }
    
  }
  par(mar = c(margins[1], 0, 0, margins[2]))
  if (!symm || scale != "none") {
    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(x = 1:nc, 
        y = 1:nr, 
        z = 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$col <- col
  # if (!invalid(na.color) & any(is.na(x))) {
  #     mmat <- ifelse(is.na(x), 1, NA)
  #    image(1:nc, 1:nr, mmat, axes = FALSE, xlab = "", ylab = "", 
  #         col = na.color, add = TRUE)
  # }
  axis(side = 1, 
       at = 1:nc, 
       labels = labCol, 
       las = 2, 
       line = -0.5, 
       tick = 0, 
       cex.axis = cexCol)
  if (!is.null(xlab)) 
    mtext(text = xlab, 
          side = 1, 
          line = margins[1] - 1.25)
  #    axis(3, 1:nc, labels = labCol, las = 2, line = -0.5, tick = 0, 
  #        cex.axis = cexCol)
  if (!is.null(xlab)) {
    mtext(text = xlab, 
          side = 3, 
          line = margins[1] - 1.25)
  }
  axis(side = 4, 
       at = iy, 
       labels = labRow, 
       las = 2, 
       line = -0.5, 
       tick = 0, 
       cex.axis = cexRow)
  if (!is.null(ylab)) {
    mtext(text = ylab, 
          side = 4, 
          line = margins[2] - 1.25)
  }
  if (!missing(add.expr)) {
    eval(substitute(add.expr))
  }
  if (!missing(colsep)) {
    for (csep in colsep) {
      rect(xleft = csep + 0.5, 
           ybottom = rep(0, length(csep)), 
           xright = csep + 0.5 + sepwidth[1], 
           ytop = rep(ncol(x) + 1, csep), 
           lty = 1, 
           lwd = 1, 
           col = sepcolor, 
           border = sepcolor)
    }
  }
  if (!missing(rowsep)) {
    for (rsep in rowsep) {
      rect(xleft = 0, 
           ybottom = (ncol(x) + 1 - rsep) - 0.5, 
           xright = nrow(x) + 1, 
           ytop = (ncol(x) + 1 - rsep) - 0.5 - sepwidth[2], 
           lty = 1, 
           lwd = 1, 
           col = sepcolor, 
           border = sepcolor)
    }
  }
  min.scale <- min(breaks)
  max.scale <- max(breaks)
  x.scaled <- scale01(t(x), min.scale, max.scale)
  if (trace %in% c("both", "column")) {
    retval$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(x = 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(x = ddc, 
         axes = FALSE, 
         xaxs = "i", 
         leaflab = "none")
  } else {
    plot.new()
  }
  if (!is.null(main)) {
    title(main = 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))
      tmpbreaks[length(tmpbreaks)] <- max(abs(x))
    } 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, "Value", line = 2)
      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$x, min.raw, max.raw)
      lines(x = dens$x, 
            y = dens$y/max(dens$y) * 0.95, 
            col = denscol, 
            lwd = 1)
      axis(side = 2, 
           at = pretty(dens$y) / max(dens$y) * 0.95, 
           labels = pretty(dens$y))
      title("")
      #title("Color Key and Density Plot", cex=0.25)
      par(cex = 0.25)
      mtext(side = 2, 
            "", 
            line = 2)
      #mtext(side = 2, "Density", line = 2)
    } else if (density.info == "histogram") {
      h <- hist(x, 
                plot = FALSE, 
                breaks = breaks)
      hx <- scale01(breaks, min.raw, max.raw)
      hy <- c(h$counts, h$counts[length(h$counts)])
      lines(x = hx, 
            y = hy/max(hy) * 0.95, 
            lwd = 1, 
            type = "s", 
            col = denscol)
      axis(side = 2, 
           at = pretty(hy)/max(hy) * 0.95, 
           labels = pretty(hy))
      #title("Color Key and Histogram", cex=0.25)
      title("", 
            cex = 0.25)
      par(cex = 0.25)
      mtext(side = 2, 
            "", 
            line = 2)
      #mtext(side = 2, "Count", line = 2)
    } else { 
      title("", 
            cex = 0.25)
      #title("Color Key", cex=0.25)
    }
  } else {
    plot.new()
  }
  
  retval$colorTable <- data.frame(low = retval$breaks[-length(retval$breaks)], 
                                  high = retval$breaks[-1], color = retval$col)
  invisible(retval)
}