ComplexHeatmap-boxplot.R

set.seed(123)
m = matrix(rnorm(100*10), nrow = 100)

# you should clustr the columns before making the heatmap because the column
# ordering will be used in `panel.fun`
column_hclust = hclust(dist(t(m)))

subgroup = sample(letters[1:3], 100, replace = TRUE, prob = c(1, 5, 10))
rg = range(m)
panel_fun = function(index, nm) {
    pushViewport(viewport(xscale = c(0.5, ncol(m) + 0.5), yscale = rg))
    grid.rect()
    grid.yaxis(gp = gpar(fontsize = 8))
    # `index` is the row order that has been reordered from hierarchical clustering,
    # but we don't have this information for the columns, so the column order
    # after clustering should be calculated in advance
    m2 = m[index, column_hclust$order, drop = FALSE]
    for(i in 1:ncol(m2)) {
    	grid.boxplot(m2[, i], pos = i)
   }
    popViewport()
}
anno = anno_zoom(align_to = subgroup, which = "row", panel_fun = panel_fun, 
    size = unit(2, "cm"), gap = unit(1, "cm"), width = unit(4, "cm"), 
    link_width = unit(1, "cm"))
# turn off `column_dend_reorder`, just to make sure the order of the `column_hclust`
# is the same as in the heatmap
Heatmap(m, name = "mat", 
	cluster_columns = column_hclust, column_dend_reorder = FALSE,
	right_annotation = rowAnnotation(foo = anno), row_split = subgroup)