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    <p><strong>EDIT</strong></p> <p>From 8 August 2011 the <code>ggdendro</code> package is available on <a href="http://cran.r-project.org/web/packages/ggdendro/index.html" rel="noreferrer">CRAN</a> Note also that the dendrogram extraction function is now called <code>dendro_data</code> instead of <code>cluster_data</code></p> <hr> <p>Yes, it is. But for the time being you will have to jump through a few hoops:</p> <ol> <li>Install the <code>ggdendro</code> package (available from CRAN). This package will extract the cluster information from several types of cluster methods (including <code>Hclust</code> and <code>dendrogram</code>) with the express purpose of plotting in <code>ggplot</code>.</li> <li>Use grid graphics to create viewports and align three different plots.</li> </ol> <p><img src="https://i.stack.imgur.com/tJtAf.png" alt="enter image description here"></p> <p>The code:</p> <p>First load the libraries and set up the data for ggplot:</p> <pre><code>library(ggplot2) library(reshape2) library(ggdendro) data(mtcars) x &lt;- as.matrix(scale(mtcars)) dd.col &lt;- as.dendrogram(hclust(dist(x))) col.ord &lt;- order.dendrogram(dd.col) dd.row &lt;- as.dendrogram(hclust(dist(t(x)))) row.ord &lt;- order.dendrogram(dd.row) xx &lt;- scale(mtcars)[col.ord, row.ord] xx_names &lt;- attr(xx, "dimnames") df &lt;- as.data.frame(xx) colnames(df) &lt;- xx_names[[2]] df$car &lt;- xx_names[[1]] df$car &lt;- with(df, factor(car, levels=car, ordered=TRUE)) mdf &lt;- melt(df, id.vars="car") </code></pre> <p>Extract dendrogram data and create the plots</p> <pre><code>ddata_x &lt;- dendro_data(dd.row) ddata_y &lt;- dendro_data(dd.col) ### Set up a blank theme theme_none &lt;- theme( panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank(), axis.title.x = element_text(colour=NA), axis.title.y = element_blank(), axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank() #axis.ticks.length = element_blank() ) ### Create plot components ### # Heatmap p1 &lt;- ggplot(mdf, aes(x=variable, y=car)) + geom_tile(aes(fill=value)) + scale_fill_gradient2() # Dendrogram 1 p2 &lt;- ggplot(segment(ddata_x)) + geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) + theme_none + theme(axis.title.x=element_blank()) # Dendrogram 2 p3 &lt;- ggplot(segment(ddata_y)) + geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) + coord_flip() + theme_none </code></pre> <p>Use grid graphics and some manual alignment to position the three plots on the page</p> <pre><code>### Draw graphic ### grid.newpage() print(p1, vp=viewport(0.8, 0.8, x=0.4, y=0.4)) print(p2, vp=viewport(0.52, 0.2, x=0.45, y=0.9)) print(p3, vp=viewport(0.2, 0.8, x=0.9, y=0.4)) </code></pre>
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    1. COvery nice. Would be nice to (1) move the legend out of the way somewhere and (2) expand the geom_tile() so it filled the whole panel (I think these are both doable, #2 internally and #1 with `ggExtra` tricks ...)
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    2. CO@BenBolker, yes indeed. This is the beauty of ggplot, isn't it? Once the data is in the desired format, one can manipulate all of the plot format...
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    3. CO@Andrie: Marvelous
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