add QC using morphology images and/or transcript coordinates
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Domain
- bioinformatics
Research direction
Start by examining the available morphology.ome.tif, morphology_focus/, and transcript z-coordinate data, then review SpatialData as a possible ingestion route. Define which raw-data features are informative and how they fit the QC pipeline; done means those features are ingested, learned, and included in QC.
Written by the indexing model from the issue text.
Description
There may be additional QC features that can be learned from other raw data, i.e. from morphology.ome.tif or morphology_focus/, or from transcript z-coordinates.
- Ingest some of this data (using SpatialData, for example)
- Learn some informative features
- Add it to QC pipeline
- Dominant language
- Jupyter Notebook
- Stars
- 7
- Forks
- 8
- PR merge metrics
- No merged PRs in 30d
Getting set up
This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.
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.
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