AliciaSchep
commented
7 years ago NucleoATAC is pretty specifically targeted towards ATAC-seq data. In the paper, we also showed it could be used for MNase, but that required using a V-plot learned from Mnase (default NucleoATAC one is from ATAC) data and also did not use the sequence bias model for ATAC (which NucleoATAC uses by default); additionally only the cross-correlation analysis was performed for MNase, and not an occupancy calculation. For a protocol with a different enzyme, I would not expect the V-plot to look the same as for ATAC-seq. NucleoATAC uses a V-plot learned from ATAC-seq as starting point, and adjusts based on fragment size of sample; doing so only makes sense if sample is also ATAC-seq. It also looks like the modelling of the fragment size did not work at all, as it doesn't seem like your sample has a mixture of NFR and nucleosome reads, as is the case for ATAC-seq.
In general, while an approach similar to what is used in NucleoATAC may be effective with your kind of data, using NucleoATAC is probably not appropriate :slightly_frowning_face:
avilella
I am trying NucleoATAC on datasets of a lab workflow similar to ATAC-seq but not quite, and I am wondering if the results I am getting make sense. Some samples have a decent looking VMat plot, e.g.:
Some others look a bit more flat/discontinuous:
The model plots for the nice looking ones seem good to me:
Does this look good? Anything I should play around with or change?