I believe that's just how it is calculated, so with the appropriate utilities and peak calls it is pretty easy to do. In our lab we have developed and studied another version of that metric, called SPOT (signal portion of tags), that computes the fraction of reads in "hotspots," which are regions of tag enrichment (like peaks, but generally more arbitrarily sized). We have analysis (still unpublished, but hopefully on its way) that shows SPOT to track pretty well for a given assay/mark with the strand correlation metric that Anshul has developed. Unlike the correlation metric, FRiP-like metrics such as SPOT obviously depend on the peak caller used, so I think the key thing is to settle on a particular peak caller and use the same settings each time in order to properly compare scores. In other words, FRiP scores computed with MACS shouldn't be compared with those computed with SPP, or with SPOT scores. However, as you've discovered, it's conceptually a pretty easy metric to understand, and we've used SPOT for our own data (DNase-seq/ChIP-seq) for several years and found it to be pretty reliable.
If you're interested, code to calculate hotspots and the SPOT metric is available here:
Bob
Hi
I'm reading the Landt 2012 paper detailing the usage of the IDR in Encode projects and I stumbled on the definition of FRip (fraction of reads in peaks). I was wondering if you know how exactly it is defined, and if a suitable package to calculate it exists. I would imagine it's simply a matter of scanning the output macs bed file to count the reads/peaks, however I still thought I'd ask if something different it's done to obtain the metrics. Thanks!