Universal Single Cell AnnotatorSAFE

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pip install cellidentifierdx

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---
name: 'universal-single-cell-annotator'
description: 'Annotate scRNA-seq'
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
  - read_file
  - run_shell_command
---


# 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 annotation columns.

## Example Usage

**User**: "Annotate this dataset looking for T-cells and B-cells."

**Agent Action**:
```python
from universal_annotator import UniversalAnnotator
import scanpy as sc

adata = sc.read_h5ad('data.h5ad')
annotator = UniversalAnnotator(adata)

markers = {
    'T-cell': ['CD3D', 'CD3E', 'CD8A'],
    'B-cell': ['CD79A', 'MS4A1']
}

annotator.annotate_marker_based(markers)
# Results in adata.obs['predicted_cell_type']
```


<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

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none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

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Findings (1)

Gates applied: no_behavioural_pass.