Tutorial for scATAC, when you also have scRNA-seq data but not in multiomics

[MariaRosariaNucera]

Hi, thank you for the wonderful tool.
I am using it, I have scATAC and scRNA-seq data but not on the same cell. I have pre-processed different samples with Cell Ranger Atac and Cell Ranger, respectively.

I am not sure about how to modify the first part of the tutorial to accomodate for the lack of cell metadata annotation.
I report what is explained in the documentation:

In case of independent scATAC-seq data, the cell annotation can also be obtained from alternative methods, such as unnanotated/preliminary clustering analysis (using predefined regions, for example SCREEN for mouse and human). In the later case, you can skip this section and use bulk regions as input to the QC step.

However, it is not totally clear to me how to proceed. Would it be possible to explain it further in the tutorial?

Do I just sostituite the "consensus_regions.bed", in this part:

path_to_regions= {'10x_no_perm': outDir + 'consensus_peak_calling/consensus_regions.bed

with the "peaks.bed" file obtained as output of Cell Ranger ATAC?

Would it make sense to analyse the scATAC data with some other standard pipeline (es the Signac one), integrate with scRNA-seq, get the barcode-celltype metadata and then on top of that run the pycisTopic pipeline as in the standard multiomic tutorial and then transferring the labels again from scRNA-seq?
I am not sure if doing pseudobulk with celltypes obtained in this way would make sense though as it seems to re-do the analysis twice.

I am happy to just use the peaks.bed as consesus_regions.bed instead, I am just not sure if it would be better to integrate the different samples somehow, but maybe this can just be done afterwards.

Thank you very much in advance.

Maria