Fseq versus MACS2 for ATAC-seq
I wish to compare two biological conditions with respect to their open chromatin. I use ATAC-seq as my assay. My strategy has thus far been to:
- call peaks on replicates of each condition
- find common peaks between replicates
- merge peaks between conditions
- count reads in peak intervals for each replicate in each condition using featuresCount
- Perform DESeq2 differential analysis between the conditions
However, when I use MACS2 I get a lot fewer peaks (-200,000) than if I use FSeq (-20,000,000). I have heard that FSeq is better for considering cutting sites as opposed to the pile-up of overlapping reads strategy that MACS uses. I was wondering, what do people generally favour? What are the benefits of using one over the other?
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Can you give some details on the species? 200k is a lot. In human, you typically get something in the range of several tens-of-thousands, depending on the q-value cutoff and stringency in downstream filtering. I cannot comment on F-Seq as I never used it, but if peak calling gives you a hard time, maybe consider the R/BioC package CSAW, which uses a window-based approach over the entire genome to call differential regions, avoiding the need to call peaks. Also, what command did you use for ATAC-seq with macs?