Hi,
I am using your R script for identification of 4C interactions. It works well on cis contacts, but because the only major criteria to call significant peaks is the existence of close contacts (as controlled by the "window.size=1" on the main "fourSig" function the program reports as significant contacts areas with 1 or 2 rpms. Is there a way to implement a latter step on the script where the contacts with no significant readnumber (<50 or something that can be estimated from bsckground noise) will be excluded?
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That's not a bad idea, and a quick way to do this would be to add pseudo-counts to each fragment. That would make the difference of 1 or 2 reads not nearly as significant.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Hi,
I am using your R script for identification of 4C interactions. It works well on cis contacts, but because the only major criteria to call significant peaks is the existence of close contacts (as controlled by the "window.size=1" on the main "fourSig" function the program reports as significant contacts areas with 1 or 2 rpms. Is there a way to implement a latter step on the script where the contacts with no significant readnumber (<50 or something that can be estimated from bsckground noise) will be excluded?
That's not a bad idea, and a quick way to do this would be to add pseudo-counts to each fragment. That would make the difference of 1 or 2 reads not nearly as significant.