Reproducing lattice dendrogram graph with ggplot2

Question

Is this possible to reproduce this lattice plot with ggplot2?

library(latticeExtra)
data(mtcars)
x  <- t(as.matrix(scale(mtcars)))
dd.row <- as.dendrog         


        

Answer 1

These links provide a solution for heatmaps with dendrograms in ggplot2:

https://gist.github.com/chr1swallace/4672065

https://github.com/chr1swallace/random-functions/blob/master/R/ggplot-heatmap.R

and also this one:

Align ggplot2 plots vertically

Answer 2

As Ben says, everything is possible. Some work to support dendrograms has been done. Andrie de Vries has made a fortify method of tree objects. However, the resulting graphic is not pretty as you can see.

The tile would be easy to do. For the dendrogram I would inspect plot.dendrogram (using getAnywhere) to see how the coordinates for the segments are calculated. Extract those coordinates and use geom_segment to plot the dendrogram. Then use viewports to plot the tiles and the dendrogram together. Sorry I can't give a example, it's a lot of work and it's too late.

I hope this helps

Cheers

Answer 3

Doubtful. I do not see any functions in the Index for ggplot2 that would suggest support for dendrograms, and when this blogger put together a set of translations of the illustrations in Sarkar's Lattice book, he was unable to get a ggplot dendrogram legend:

http://learnr.wordpress.com/2009/08/10/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-part-9/

Answer 4

EDIT

From 8 August 2011 the ggdendro package is available on CRAN Note also that the dendrogram extraction function is now called dendro_data instead of cluster_data

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Yes, it is. But for the time being you will have to jump through a few hoops:

1. Install the ggdendro package (available from CRAN). This package will extract the cluster information from several types of cluster methods (including Hclust and dendrogram) with the express purpose of plotting in ggplot.
2. Use grid graphics to create viewports and align three different plots.

The code:

First load the libraries and set up the data for ggplot:

library(ggplot2)
library(reshape2)
library(ggdendro)

data(mtcars)
x <- as.matrix(scale(mtcars))
dd.col <- as.dendrogram(hclust(dist(x)))
col.ord <- order.dendrogram(dd.col)

dd.row <- as.dendrogram(hclust(dist(t(x))))
row.ord <- order.dendrogram(dd.row)

xx <- scale(mtcars)[col.ord, row.ord]
xx_names <- attr(xx, "dimnames")
df <- as.data.frame(xx)
colnames(df) <- xx_names[[2]]
df$car <- xx_names[[1]]
df$car <- with(df, factor(car, levels=car, ordered=TRUE))

mdf <- melt(df, id.vars="car")

Extract dendrogram data and create the plots

ddata_x <- dendro_data(dd.row)
ddata_y <- dendro_data(dd.col)

### Set up a blank theme
theme_none <- 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 <- ggplot(mdf, aes(x=variable, y=car)) + 
  geom_tile(aes(fill=value)) + scale_fill_gradient2()

# Dendrogram 1
p2 <- 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 <- ggplot(segment(ddata_y)) + 
  geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) + 
  coord_flip() + theme_none

Use grid graphics and some manual alignment to position the three plots on the page

### 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))