cellchat - Cell-cell communication analysis with CellChat
Analyzes, visualizes, and compares ligand-receptor communication networks from single-cell or spatial transcriptomics data.
Tags
Updated: 2026-10-08Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Build CellChat objects
- Infer ligand-receptor communication
- Aggregate pathway signals
- Analyze signaling centrality
- Discover communication patterns
- Compare communication datasets
- Lift across cell compositions
- Visualize communication networks
- Cluster pathway similarity
Inputs
- Annotated Seurat object
- SingleCellExperiment object
- Counts matrix
- Cell-level metadata
- Cell-type labels
- Species selection
- Signaling category
- Condition-specific datasets
Outputs
- Annotated CellChat object
- Ligand-receptor probabilities
- Pathway-level probabilities
- Permutation p-values
- Aggregated communication matrices
- Signaling centrality scores
- Communication network plots
- Comparison plots and tables
- CellChat RDS files
Requirements
- R 4.1 or later
- CellChat R package
- ComplexHeatmap package
- NMF package
- circlize package
- Seurat v4 or v5 for Seurat inputs
- umap-learn for embedding plots