 I have some ``ATAC-seq PE`` samples and `Dnase-seq SE` samples, I like to do peak calling for them using MACS2.  I run MACS2 command with `--nomodel -- shift -100 -- extsize 200 ` For DNase samples but for ATAc seq samples I am not sure    which one of `--nomodel -- shift -100 -- extsize 200 ` or  only use ` -f BAMPE` options of MACS2 is better? 


Also, I found in ENDCODE https://docs.google.com/document/d/1f0Cm4vRyDQDu0bMehHD7P7KOMxTOP-HiNoIvL1VcBt8/edit part 2a, that use bed file but there 2 files BEDPEand TAG file

-tagAlign file ${FINAL_TA_FILE}

-BEDPE file (with read pairs on each line) ${FINAL_BEDPE_FILE}

-Subsampled tagAlign file for CC analysis ${SUBSAMPLED_TA_FILE}

that I am not sure which one should be use as Input of MACS2. should I use TAG file as Input?
The [official Harvard guidelines][1] as of this year suggest the following:

> Our previous recommendation was to run MACS2 with -f BAMPE, which is
> similar to the default analysis mode of Genrich (inferring full
> fragments, rather than cut site intervals). Others have attempted to
> interpret cut site intervals with MACS2 by using the --shift and
> --extsize arguments, but these arguments are ignored in BAMPE mode. They do work in the default (BAM) mode, but then, with paired-end
> reads, most of the alignments are automatically discarded (half of the
> properly paired alignments and all of the unpaired alignments;
> secondary alignments are never considered). Is it worse to interpret
> full fragments that may be less informative biologically, or to
> disregard more than half of the sequence data? A complicated question.
> The correct answer is: use Genrich.

The main issue with `--nomodel -- shift -100 -- extsize 200 -f BAM` is that you lose a lot of reads (approx 50%). As the MACS2 manual states specifically that for the `-f BAM` parameter:

> If the BAM file is generated for paired-end data, MACS will only keep
> the left mate(5' end) tag."

So you lose all your 3' information.

If you are interested you could read the [old Harvard guidelines which do cover the optimal parameters for using MACS2][2].


  [1]: https://informatics.fas.harvard.edu/atac-seq-guidelines.html
  [2]: https://informatics.fas.harvard.edu/atac-seq-guidelines-old-version.html