CellDialog: A Computational Framework for Ligand-receptor-mediated Cell-cell Communication Analysis III

Area of Science:

• Computational biology
• Systems biology
• Bioinformatics

Background:

• Intercellular communication is crucial for tumor progression, metastasis, and therapy resistance.
• Accurate inference of intercellular communication requires robust ligand-receptor interaction (LRI) databases and strength measurement methods.

Purpose of the Study:

• To develop a computational framework, CellDialog, for reconstructing intercellular connectivity networks.
• To accurately infer and visualize LRI-mediated intercellular communication.

Main Methods:

• CellDialog employs LRI feature extraction, selection, and classification to identify high-confidence LRIs.
• It utilizes a three-point estimation approach combining LRI filtering and single-cell RNA sequencing (scRNA-seq) data to quantify communication strength.
• The framework offers heatmap and network visualizations for intercellular communication.

Main Results:

• CellDialog successfully reconstructs intercellular connectivity networks.
• Comparison analysis demonstrates CellDialog's efficiency in decoding intercellular communications compared to other tools.
• The framework provides visualization tools for analyzing intercellular signal transduction.

Conclusions:

• CellDialog is an effective computational tool for reconstructing and analyzing intercellular communication networks.
• The framework enhances the understanding of LRI-mediated signaling in biological systems.
• CellDialog is freely available, facilitating broader research in intercellular communication analysis.