Connectome

Connectome computes cell-cell signaling networks from single-cell RNA-sequencing (scRNA-seq) data to quantify and visualize ligand-receptor interactions underlying tissue and organ functionality.

Key Features:

• Rapid network computation: Calculates cell-cell signaling network topologies derived from scRNA-seq data.
• Ligand-receptor compatibility: Works with any reference set of known ligand-receptor mechanisms.
• Differential and comparative connectomics: Performs differential and comparative analyses to quantify differences between mechanistic networks across biological systems.
• Computational and graphical analysis tools: Provides computational routines and graphical visualization capabilities for exploring connectivity patterns across single-cell datasets.

Scientific Applications:

• Network quantification and visualization: Quantifies and visualizes intricate cell-cell signaling networks and ligand-receptor interactions from scRNA-seq data.
• Comparative analysis of conditions: Compares connectivity patterns between different biological contexts or experimental conditions.
• Hypothesis investigation: Investigates how ligand-receptor interactions influence cellular behavior and tissue organization at the single-cell level.

Methodology:

Computational methods explicitly include calculating cell-cell signaling network topologies from scRNA-seq, using reference ligand-receptor mechanism sets, performing differential and comparative network analyses, and producing graphical visualizations.