script_heatmap.R

library(fastcluster)
library(gplots)

script.plot<-function(fp,n,K,pngfile)
{
    set.seed(0)
    id<-sample.int(nrow(fp$x),n)
    cid<-cbind(fp=fp$peaks.cluster)
    plotdata(fp$x,K,cid,id=id,pngfile=pngfile,
             cols=NULL)
}

gencols<-function(n,type="rainbow")
{
    jet.colors <-
    colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan",
                       "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"))
    res<-switch(type,
                jet.cols=jet.colors(n),
                rainbow=rainbow(n))
    if(is.null(res)){
        stop("type is not correct\n")
    }
    res
}
plotdata<-function(x,hK=10,cid=NULL,n0=4000,id=NULL,pngfile=NULL,cols=NULL) #n should be around 2000 to 4000
{
    myfunc<-function(d){
        fastcluster::hclust(d,method="ward")
    }
    mydist<-function(x){
        dist(x)^2
    }
    scale01 <- function(x, low = min(x), high = max(x)) {
        x <- (x - low)/(high - low)
        x
    }
    if(is.null(pngfile)){
        pngfile<-"plot.png"
    }
    png(pngfile,width=1400,height=1200,res=400,pointsize=10) #
    n<-nrow(x)
    if(is.null(id)){
        if(n<n0){
            id<-1:n
        }else{
            id<-sample.int(n,n0)
        }
    }
    y<-t(x[id,])
    ##note that y has been rotated
    nc<-ncol(y)
    nolab<-rep("",ncol(y))
    lmat<-matrix(c(3,2,1,-1),byrow=TRUE,ncol=2)
    nmat<-3
    if(!missing(hK)){
        ##nmat<-nmat+1
        ##lmat<-rbind(lmat[1,],c(nmat,0),lmat[-1,])
        lmat<-rbind(lmat[1,],c(nmat+1,nmat+2),lmat[-1,])
        nmat<-nmat+2
    }
    ##lmat<-rbind(lmat[1,],cbind((nmat+1):(nmat+ncol(cid)),0),lmat[-1,])
    lmat<-rbind(lmat[1,],nmat+cbind(1:(2*ncol(cid)-1),2*(1:ncol(cid))),
                lmat[-1,])
    lmat[lmat==-1]<-max(lmat)+1 #-1 is for the key and was drawn last
    
    lhei<-c(5,rep(1,nrow(lmat)-2),10)
    lwid<-c(10,2)
    col<-gencols(16,"jet.cols")
    margins<-c(5,5)
    op <- par(no.readonly = TRUE)
    on.exit(par(op))
    ret<-heatmap.2.ge(y,col=col,hclustfun=myfunc,distfun=mydist,margins=margins,
                   trace="none", key=FALSE,labCol=nolab,
                   dendrogram="col",lmat=lmat,lhei=lhei,lwid=lwid,
                   breaks=17,cexRow=1)

    if(!missing(hK)){
        cc<-gencols(hK)[cutree(as.hclust(ret$colDendrogram),hK)]
        cc<-cc[ret$colInd]
        par(mar = c(0.2, margins[1],0.2,0.1))
        image(t(rbind(1:nc)), col = cc, axes = FALSE)
        axis(2, 0, labels = "hclust",
             las = 2, line = -0.5, tick = 0, 
             cex.axis = 1)
        #draw the legend
        par(mar = c(0.8,0.3,0.4,0.3))
        image(t(rbind(1:hK)),col=gencols(hK),breaks=(0:hK)+0.5,xaxt = "n", yaxt = "n")
        par(usr = c(0, 1, 0, 1))
        lv <- c(1,hK)
        xv <- scale01(as.numeric(lv), 0.5, hK+0.5)
        par(mgp=c(-0.1,-0.4,0))
        axis(1, at = xv, labels = lv,las=1,cex.axis=0.5,tick=FALSE)
    }


    #draw cid
    if(!is.null(cid)){
        for(j in 1:ncol(cid)){
            cidj<-cid[id,j][ret$colInd]
            if(is.null(cols)){
                cols<-rep("black",length(cidj))
                cols<-gencols(max(cidj))
            }
            cc<-rep("black",length(cidj))
            K<-max(cidj) ##asuming from 1, 2, 3, ..., where 0 indicates outliers
            idval<-cidj>0
            cc[idval]<-cols[cidj[idval>0]]
            
            par(mar = c(0.2,margins[1], 0.2, 0.1))
            image(t(rbind(1:nc)), col = cc, axes = FALSE)
            par(mgp=c(3,1,0))
            axis(2, 0, labels = colnames(cid)[j],
                 las = 2, line = -0.5, tick = 0, 
                 cex.axis = 1)

            #draw the legend
            par(mar = c(0.8,0.3,0.4,0.3))
            image(t(rbind(1:K)),col=cols[1:K],breaks=(0:K)+0.5,xaxt = "n", yaxt = "n")
            #axis(1,at=c(1,K),labels=c(1,K))
            par(usr = c(0, 1, 0, 1))
            lv <- c(1,K)
            xv <- scale01(as.numeric(lv), 0.5, K+0.5)
            par(mgp=c(-0.1,-0.4,0))
            axis(1, at = xv, labels = lv,las=1,cex.axis=0.5,tick=FALSE)
        }
    }
    ##draw the key
    par(mar = c(0.5,1.5,0.5,2.5), cex = 0.75)
    breaks <- ret$breaks
    min.raw <- min(y, na.rm = TRUE)
    max.raw <- max(y, na.rm = TRUE)
    z <- seq(min.raw, max.raw, length = length(col))
    image(z = t(matrix(z, ncol = 1)), col = col, breaks = breaks, 
          xaxt = "n", yaxt = "n")
    par(usr = c(0, 1, 0, 1))
    lv <- pretty(breaks)
    xv <- scale01(as.numeric(lv), min.raw, max.raw)
    par(mgp=c(3,0.37,0))
    axis(4, at = xv, labels = lv)
    
    #draw the hclust results
    dev.off()
}
##this function is based on the heatmap.2 with some modfications
heatmap.2.ge<-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
    }
    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,mean)
        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,mean)
        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.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)

    ##no bother with the following
    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(0.1,margins[1], 0.5, 0.1)) #modified
    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$col <- col
    if (!invalid(na.color) & any(is.na(x))) {
        mmat <- ifelse(is.na(x), 1, NA)
        image(1:nc, 1:nr, mmat, axes = FALSE, xlab = "", ylab = "", 
            col = na.color, add = TRUE)
    }
    axis(1, 1:nc, labels = labCol, las = 2, line = -0.5, tick = 0, 
        cex.axis = cexCol)
    if (!is.null(xlab)) 
        mtext(xlab, side = 1, line = margins[1] - 1.25)
    axis(2, iy, labels = labRow, las = 2, line = -0.5, tick = 0, 
        cex.axis = cexRow)
    if (!is.null(ylab)) 
        mtext(ylab, side = 2, line = margins[1] - 1.25) #modified
    if (!missing(add.expr)) 
        eval(substitute(add.expr))
    if (!missing(colsep)) 
        for (csep in colsep) rect(xleft = csep + 0.5, ybottom = rep(0, 
            length(csep)), xright = csep + 0.5 + sepwidth[1], 
            ytop = rep(ncol(x) + 1, csep), lty = 1, lwd = 1, 
            col = sepcolor, border = sepcolor)
    if (!missing(rowsep)) 
        for (rsep in rowsep) rect(xleft = 0, ybottom = (ncol(x) + 
            1 - rsep) - 0.5, xright = nrow(x) + 1, ytop = (ncol(x) + 
            1 - rsep) - 0.5 - sepwidth[2], lty = 1, lwd = 1, 
            col = sepcolor, border = sepcolor)
    min.scale <- min(breaks)
    max.scale <- max(breaks)
    x.scaled <- scale01(t(x), min.scale, max.scale)
    if (trace %in% c("both", "column")) {
        retval$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)
    if (dendrogram %in% c("both", "row")) {
        par(mar = c(0.1,margins[1],0.1, 0.1)) #modified
        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")) {
        par(mar = c(0.1,margins[1],0.1, 0.1))  #modified
        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, "Value", 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() #this is disruptive
    }
    retval$colorTable <- data.frame(low = retval$breaks[-length(retval$breaks)], 
        high = retval$breaks[-1], color = retval$col)
    invisible(retval)
}