Regressing out variables in pearson residual normalization (SCTransform)
Open
Nobody has claimed this yet.
Needs info❔
- Dominant language
- Python
- Stars
- 2.6k
- Forks
- 779
- Avg merge
- 1d 4h
- Merged PRs (30d)
- 27
Description
What kind of feature would you like to request?
Additional function parameters / changed functionality / changed defaults?
Please describe your wishes
Perhaps the regress_out function within the Pearson residual normalization pipeline would be beneficial.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by inspecting the regress_out function within the Pearson residual normalization pipeline and the surrounding SCTransform entry point. Clarify which variables, parameters, and behavior should be supported, then add tests that define the intended regression results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- bioinformatics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100