hic_circlize.R

library(GenomicInteractions)
data(hic_example_data)

hic_example_data = as.data.frame(hic_example_data)

hic_example_data = hic_example_data[hic_example_data$seqnames1 == hic_example_data$seqnames2, ]


gr1 = hic_example_data[, c("seqnames1", "start1", "end1")]
colnames(gr1) = c("chr", "start", "end")
gr2 = hic_example_data[, c("seqnames2", "start2", "end2")]
colnames(gr2) = c("chr", "start", "end")

gr = rbind(gr1, gr2)
gr = unique(gr)

library(circlize)



hic_heatmap = function(pos11, pos12, pos21, pos22, col) {
	mid1 = (pos12 + pos11)/2
	mid2 = (pos22 + pos21)/2
	dist = abs((mid2 - mid1)/2)
	x = (mid2 + mid1)/2
	y = dist/2
	w = ((pos22 - pos21) + (pos12 - pos11))/2
	h = w
	circos.rect(x - w/2, y - h/2, x + w/2, y + h/2, col = col, border = col)
}

circos.genomicInitialize(gr)
df = hic_example_data
df = df[abs(df$start2 - df$start1) <= 1000000, ]
col_fun = colorRamp2(c(min(df$Z.score), mean(df$Z.score), max(df$Z.score)),
	                 c("red", "white", "blue"))
circos.track(ylim = c(0, max(abs(df$start2 - df$start1))/2), 
	panel.fun = function(x, y) {
		df2 = df[df$seqnames1 == CELL_META$sector.index, ]
		hic_heatmap(df2$start1, df2$end1, df2$start2, df2$end2, col_fun(df2$Z.score))
	})