scverse / scverse/SnapATAC2

Using SCENIC+ with clustered and annotated anndataset

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Python
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Description

Hi,
Thank you for this amazing tool! I am working with snapATAC2 to do multi-sample analysis and have successfully processed the data and called peaks. I would like to do GRN analysis using SCENIC+ at this point. In the paper, it was mentioned that snapATAC2 integrate well with SCENIC+. I was wondering how that process would look like? SCENIC+ FAQs for Signac and ArchR indicate that completely processed data use, without modeling using pycisTopic, has not been tested before and is highly dependent on DAR calling. Therefore, I am confused.

Can I use marker regions as DARs here (obtained using tl.marker_regions) and the peak matrix? If yes, what would be a good substitution for Topics? Also, is there a function to convert the tl.motif_enrichment results to cistrome?

Thank you for your help!

Best,
Ananya

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the SCENIC+, snapATAC2, pycisTopic, Signac, and ArchR workflow references mentioned in the issue. Check how tl.marker_regions, the peak matrix, and tl.motif_enrichment relate to DARs, topics, and cistromes. Done would require a documented, supported workflow or explicit guidance for this processed-data use case.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
bioinformatics
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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