Preprocessing and Visualization
Includes functions for data normalization, log transformation, and multiple embedding techniques such as PCA, t-SNE, UMAP, force-directed graph drawing, and diffusion maps.
Clustering and Trajectory Inference
Provides clustering algorithms including Leiden and hierarchical clustering, and trajectory inference based on geodesic distances along graphs.
Marker Gene and Gene Scoring Analysis
Supports ranking of marker genes characterizing groups, filtering genes by criteria, gene scoring, and cell cycle scoring.
Data Integration
Enables mapping of labels and embeddings from reference datasets to new data for integrated analysis.
Scalability and Ecosystem Integration
Handles datasets with more than one million cells efficiently and integrates with related tools like Squidpy and Muon within the Scanpy ecosystem.