universal-single-cell-annotator
A unified interface for annotating single-cell RNA-seq data using Marker Genes, Deep Learning (CellTypist), or LLMs.
npx skills add majiayu000/claude-skill-registry --skill rna --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Universal Single-Cell Annotator This skill wraps multiple cell type annotation strategies into a single Python class. It allows agents to flexibly choose between rule-based (markers), data-driven (CellTypist), or reasoning-based (LLM) approaches depending on the context. ## When to Use This Skill * **Initial Analysis**: When processing raw AnnData objects. * **Validation**: When cross-referencing automated labels with known markers. * **Discovery**: When identifying rare cell types using LLM reasoning on marker lists. ## Core Capabilities 1. **Marker-Based Scoring**: Scores cells based on provided gene lists (e.g., "T-cell": ["CD3D", "CD3E"]). 2. **Deep Learning Reference**: Wraps `celltypist` to transfer labels from massive atlases. 3. **LLM Reasoning**: Extracts top markers per cluster and constructs prompts for LLM interpretation. ## Workflow 1. **Load Data**: Ensure data is in `AnnData` format (standard for Scanpy). 2. **Choose Strategy**: * Use **Markers** if you have a known gene panel. * Use **CellTypist** for broad immune/tissue profiling. * Use **LLM** for novel clusters. 3. **Annotate**: Run the corresponding method. 4. **Inspect**: Check `adata.obs` for the new annotat
- When to Use This Skill
- Core Capabilities
- Workflow
- Example Usage
What does the universal-single-cell-annotator skill do?
A unified interface for annotating single-cell RNA-seq data using Marker Genes, Deep Learning (CellTypist), or LLMs.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rna --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.