Enhance Clustering Resolution Selection with Hierarchical Tree Visualization
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- Dominant language
- Python
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Description
What kind of feature would you like to request?
Additional function parameters / changed functionality / changed defaults?
Please describe your wishes
To assist users in selecting the appropriate clustering resolution and understanding the key genes driving cluster splits, implement a hierarchical tree visualization. This tree should illustrate how clusters evolve as the resolution increases, with each child node representing a finer cluster derived from its parent. Additionally, label each child node with the main driving genes that differentiate it from its parent cluster.
The result shown as
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
No files, tests, or entry points are named in the issue, so first locate the clustering-resolution and visualization entry points in Scanpy. Review how clusters change across resolutions and identify the existing analysis outputs that could support the requested tree. Done means users can view hierarchical cluster splits with each child labeled by genes differentiating it from its parent.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- bioinformatics, data-visualization
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100