Scanpy-Complete Skill

Comprehensive assistance with Scanpy - the scalable toolkit for analyzing single-cell gene expression data in Python. This skill provides complete coverage of Scanpy's preprocessing, visualization, clustering, trajectory inference, and differential expression testing capabilities.

When to Use This Skill

This skill should be triggered when:

Core Single-Cell Analysis Tasks

• Preprocessing and quality control - filtering cells/genes, normalization, highly variable gene selection
• Dimensionality reduction - PCA, UMAP, t-SNE, diffusion maps
• Clustering and community detection - Leiden, Louvain, hierarchical clustering
• Differential expression analysis - finding marker genes, statistical testing
• Trajectory inference - pseudotime analysis, RNA velocity, fate mapping
• Data integration - batch correction, merging datasets, harmonization