What kind of tool would be appropriate do detect "broad peaks" in small RNA-seq sequencing data?
MACS2 appears to be developed for ChIP-seq data, but I see that there is a
--nomodel option. Would that make this program usable in my case?
I suppose I should also set the
--extsize options, but I'm not sure how:
--nomodel Whether or not to build the shifting model. If True, MACS will not build model. by default it means shifting size = 100, try to set extsize to change it. DEFAULT: False --shift SHIFT (NOT the legacy --shiftsize option!) The arbitrary shift in bp. Use discretion while setting it other than default value. When NOMODEL is set, MACS will use this value to move cutting ends (5') towards 5'->3' direction then apply EXTSIZE to extend them to fragments. When this value is negative, ends will be moved toward 3'->5' direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with EXTSIZE option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can't set values other than 0 if format is BAMPE for paired-end data. DEFAULT: 0. --extsize EXTSIZE The arbitrary extension size in bp. When nomodel is true, MACS will use this value as fragment size to extend each read towards 3' end, then pile them up. It's exactly twice the number of obsolete SHIFTSIZE. In previous language, each read is moved 5'->3' direction to middle of fragment by 1/2 d, then extended to both direction with 1/2 d. This is equivalent to say each read is extended towards 5'->3' into a d size fragment. DEFAULT: 200. EXTSIZE and SHIFT can be combined when necessary. Check SHIFT option
In my case the tags are the same things as the fragments, so this "extension" thing is probably not appropriate.
Basically, I would like to call peaks based on the plain real coverage of my small reads. Are there other tools that would be more appropriate?