Hello,

I would be grateful if you could help me understand the functions better.

I created bed file A and B and genome, all of which have 3 peaks in exactly the same region. They look like this. Chr1 1 10
Chr2 100 150
Chr3 2 3
A and B are the ChIP peaks between which I would like to compare the similarity, and genome is the known TF map-able region.

The number of overlaps are 3 as expected, but when I run AvsB <- permTest(A=A, B=B, ntimes=10, randomize.function=randomizeRegions, evaluate.function=numOverlaps, count.once=TRUE, genome=genome) I get 0s and 1s and 2s for AvsB[["numOverlaps"]][["permuted"]]. I thought since reads in A could only map onto "genome" region and that is where peaks from B are, it would always be 3.

Do you have any ideas why this could be? Thank you so much!

Hi @shoko

I think the numbers you are seeing are the expected result (mostly). Randomize regions will randomly place the regions into the available genome, possibly overlapping (see ?randomizeRegions). This means that the 3 regions might end up in chr2, and in fact this is what happens most of the time if you test it with

A <- toGRanges(c("chr1:1-10", "chr2:100-150", "chr3:2-3"))
randomizeRegions(A=A, genome=A)

then, since you have set "count.once=TRUE", only one overlap per region in B will be reported, so most of the time it will be a 1.

This will explain the 1's, 2's and 3's, but it does not explain the 0's. In this case, this is due to a limitation of randomizeRegions, which can only work with genomes whose chromosomes start at 1. Therefore, in this case some of the random regions might appear in the chr2:1-99 region, which in theory is out of the genome. Take into account that this situation is only found in strange cases like yours (custom toy mini-genome) and some advanced usages but will not affect most use cases.

In any case, we've added a note in randomizeRegions documentation stating that and we'll try to fix it in next release of regioneR.

Hope this helps