Single-cell CellPhoneDB communication mapping

What problem does it solves? Understanding how different cell types communicate through ligand-receptor interactions is vital for biological insights, but analyzing these networks from single-cell data can be complex and time-consuming. This Skill automates CellPhoneDB analysis and visualization, making it easier to uncover cellular crosstalk.

Core Features & Use Cases

• Ligand-Receptor Interaction Inference: Quantify communication between annotated single-cell populations using CellPhoneDB v5.
• CellChat-Style Visualization: Generate intuitive network visualizations, including circle, chord, and heatmap plots.
• Pathway-Specific Analysis: Summarize global communication strength and identify significant signaling pathways.
• Signaling Role Analysis: Evaluate incoming and outgoing signaling roles of different cell types.
• Use Case: Analyze a single-cell dataset of the tumor microenvironment, identify key ligand-receptor interactions between immune cells and tumor cells, and visualize the most significant signaling pathways using chord and bubble plots.

Quick Start

Run CellPhoneDB on my single-cell data with 'cell_labels' as cell types, then visualize the aggregated communication network and specific signaling pathways.