I'm trying to figure out what tools most people use for differential chromatin detection among samples (condition1 vs condition2).
I normally use diffReps for differential detection for ChIP-seq but haven't done it for ATAC. Any suggestions?

1. Call the peaks, by merging all the replicates (bam files), with very less stringent criteria ( p-value of 0.1 ) such that you end up with union of regions ( peaks ) across two biological conditions, that have some signal enrichment. 

2. Now either use the entire peak or center the peaks on summit with +/- 200bp and count the number of reads with in each peak from all replicates independently using featureCounts. ( You can easily covert the above `bed` file to `saf` format )

        awk -v OFS = "\t" 'BEGIN { print "PeakID", "Chr", "Start", "End", "Strand" } { print "Peak_"NR, $1, $2, $3, "." }' test.bed > test.saf

3. Feed this matrix to DESeq2 or edgeR and get differential peaks. **Do some filtering of peaks like removing peaks that have very few counts across replicates, otherwise this will be a problem for multiple testing correction to include so many peaks .** 

**Edit:**

Most of the differential binding tools run either DESeq or edgeR in the back end and they are suitable for TFs, as the signal is sharp with out any noise.

But with ATAC, the peaks have both characters of TF and histone modifications.

I would 

    1. Run macs2 with p-value of 0.1 

    2. Use the narrowPeaks file, either the entire peak (Better)or take +/- 200bp from the summit (only if peaks called with --summit option in MACS, so that broad peaks are split into multiple sub-peaks).

    3. Quantify peaks using featureCounts.

    4. Feed the matrix to DESeq2.

**You should also upload this file ( from step 2 ) to browser to get a feel of how the regions that you are using for DE analysis looks like. Most likely they will be okay.**