Scanpy is a tool for studying single cells by looking at their gene activity. It helps researchers clean up their data, find patterns, and group similar cells together. Anyone working with single-cell data can use Scanpy to make sense of complex information.
The pipeline covers quality control, normalization, dimensionality reduction like PCA and UMAP, clustering, and visualization. It also converts files from R-based tools into a format Scanpy can read. This makes it easy to explore and compare single-cell data from different sources.
Researchers and data scientists use Scanpy for everyday single-cell analysis. It is designed for established workflows and works best with smaller to medium-sized datasets. For more advanced deep learning models, a different tool is recommended.
Add Scanpy skill to your workflow
Global
mkdir -p ~/.claude/skills/scanpyProject
mkdir -p .claude/skills/scanpySource Repository
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