ICELLNET

ICELLNET infers and quantifies cell–cell communication from single or multiple cell-based transcriptomic profiles by mapping ligand–receptor interactions to dissect intercellular signaling.

Key Features:

• Expert-Curated Ligand–Receptor Database: An original expert-curated database catalogs ligand–receptor interactions and accounts for the expression of multiple subunits.
• Quantification of Communication Scores: Computes quantitative communication scores between cell populations to assess interaction strength and significance.
• Integration with Reference Cell Types: Connects a cell population of interest to 31 reference human cell types sourced from BioGPS.
• Compatibility with Single or Multiple Profiles: Applies to single or multiple cell-based transcriptomic profiles for comparative and context-specific analyses.
• Three Visualization Modes: Provides three distinct visualization modes to support biological interpretation of inferred communication networks.

Scientific Applications:

• Breast cancer-associated fibroblast (CAF) analysis: Uncovered nuanced differences in intercellular communication among subsets of CAFs in breast cancer.
• Dendritic cell IL-10 autocrine signaling: Identified autocrine IL-10 signaling as a regulator of human dendritic cell communication with up to 12 other cell types, with four interactions experimentally validated.

Methodology:

Uses an expert-curated ligand–receptor database that accounts for multi-subunit expression, quantifies communication scores between cell populations, integrates profiles with 31 BioGPS reference human cell types, and presents results via three visualization modes.