tsne vs umap with square root/pearson residue normalization
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Description
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Hey, I really don't know if this could be called an issue.
Since in the paper justifying square root normalization for visualization and clustering? and the Pearson residue normalizes and select hvgs, both of the results are projected onto tSNE space. Are you suggesting we use tSNE as a major distance projection method?
Best,
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Research direction
Start by reading the linked square-root normalization and Pearson residual papers, then compare their use of tSNE with UMAP in Scanpy's documentation or analysis entry points. The issue does not name files, tests, or a concrete change, so the expected outcome is not defined.
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Assessment
- Tech stack
- python
- Domain
- bioinformatics, data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100