An introduction to the gapmap package

2 September 2014

This document explains basic functions of the gapmap package to draw a gapped cluster heatmap. The plot is generated using the ggplot2 package. Let’s load the library first.


We will simulate a simple dataset.

x <- rnorm(10, mean=rep(1:5, each=2), sd=0.4)
y <- rnorm(10, mean=rep(c(1,2), each=5), sd=0.4)
dataFrame <- data.frame(x=x, y=y, row.names=c(1:10))
#calculate distance matrix. default is Euclidean distance
distxy <- dist(dataFrame)
#perform hierarchical clustering. default is complete linkage.
hc <- hclust(distxy)
dend <- as.dendrogram(hc)

To make a gapped cluster heatmap, you need to pass a matrix object for heatmap, and dendrogram class objects for drawing dendrograms and ordering.

grey_scale =c("#333333", "#5C5C5C", "#757575", "#8A8A8A", "#9B9B9B", "#AAAAAA", "#B8B8B8", "#C5C5C5", "#D0D0D0", "#DBDBDB", "#E6E6E6")
gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend, col = grey_scale)
## Warning: The `panel.margin` argument of `theme()` is deprecated as of ggplot2 2.2.0.
## ℹ Please use the `panel.spacing` argument instead.
## ℹ The deprecated feature was likely used in the gapmap package.
##   Please report the issue at
##   <>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

The default of gapmap function is in the quantitative mode and uses exponential mapping. First, you can choose either modes: quantitative or threshold.

The following example uses the linear mapping. This mapping generate more gaps, whereas the previous example of exponential mapping emphasize on the large gaps.

gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend,  mode = "quantitative", mapping="linear", col = grey_scale)

The following example illustrate the difference of two mapping schemes. For the exponential mapping, the scale log base is set to 0.5.

The variation of scale log base settings is illustrated in the following plot. The value of scale is annotated on the plot.

Besides the quantitative mode, there is linear mode to introduce gap by a threshold. In the following example, the dendrograms for rows and columns are cut at the threshold distance of 2 and gaps of the same size are introduced between clusters.

gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend,  mode = "threshold", row_threshold = 2, col_threshold = 2, col = grey_scale)

In addition, this package works well with our dendrogram sorting package, called dendsort. For the details on dendsort, please check our paper.

gapmap(m = as.matrix(distxy), d_row= rev(dendsort(dend)), d_col=dendsort(dend),  mode = "quantitative", col = grey_scale)