I have a wide dataframe of a single row with a binary present absence dataset encoded in 1s and 0s:
dim(preMicroCazyme_wide)
[1] 1 1970
I am wanting to do this as i will layer several circos.heatmaps to show the presence absence in different systems. However the plots just come out all one colour and seemingly ignore the 0 values:
Each of the below have the same dimensions just different profiles of 1s and 0s.
cols1 = colorRamp2(c(0, 1), c("white", "blue"))
cols2 = colorRamp2(c(0, 1), c("white", "pink"))
circos.heatmap(preMicroCazyme_wide, cols1 = cols, split = FALSE, cluster = FALSE)
circos.heatmap(wide_termite_cazy, col = cols2, split = FALSE, cluster = FALSE)
# Showing the output is not correct for some reason
length(preMicroCazyme_wide[preMicroCazyme_wide == 0])
[1] 281
> length(wide_termite_cazy[wide_termite_cazy == 0])
[1] 1289
Yet the resulting plot looks like this:
This looks like the 0 values are either being ignored or coloured in regardless. Any idea how I can fix this?
Example data could look like this:
df = t(data.frame(row1 = rep(c(0,1), 100,)))