Thanks Devon. Yes of course I'll take the right cell type. When you say areas with similar mappability, what do you mean?
Hi,
I've a bunch of genomic positions and I want to check if these positions are enriched in TF binding sites or enchancer ? My idea was to use ENCODE data and to do a simulation like this :
- If I have N positions in my input list -> pick N random genomic positions and compute a score by checking in ENCODE data
- Do that 100000 times and compute a p-value = #(random score) >= real score / N
What do you think ? Other ideas ?
Thanks
1 answer
- Be sure to use only areas with similar mappability and possibly GC characteristics (there could be a bias there).
- That's the normal way to do it.
This is how I'd approach the problem as well. One thing to keep in mind is that enhancers and promoters can be cell-type specific. In an ideal world, you'd just want to look in your cell-type of interest. Also, do make sure that regions have evolutionary conservation (i.e., try not to make the same mistakes as ENCODE). A final thing to think about is whether it makes sense to look at TF binding site in toto or whether it makes sense to just look at individual transcription factors. I say this since the meaningfulness of the results there's a slight enrichment due to complete enrichment of one or two TF binding motifs vs. a generic mild enrichment of everything (i.e., a slight but significant global enrichment is likely due simply to an uncompensated bias).
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