scSeqComm

scSeqComm identifies, quantifies, and functionally characterizes cellular communication from single-cell RNA sequencing (scRNA-seq) data by integrating intercellular ligand–receptor expression and intracellular signaling pathways.

Key Features:

• Intercellular and Intracellular Signaling Analysis: Incorporates intercellular ligand–receptor expression and intracellular signaling pathway information to infer cellular communication.
• Quantification and Prioritization: Quantifies evidence of ongoing cellular communication and enables prioritization of interactions by significance.
• Functional Characterization: Provides functional characterization of inferred communications to link signaling pathways to biological roles.
• Robustness and Validation: Validated on tumor microenvironment datasets and spatial transcriptomics, with agreement to independent bioinformatics analyses and comparisons to state-of-the-art intercellular scoring schemes highlighting superior performance.

Scientific Applications:

• Tumor Microenvironment Studies: Uncovers complex signaling networks in tumor microenvironments that may contribute to cancer progression and response to therapies.
• Cellular Communication Research: Supports analysis of cellular interactions within tissues or during disease processes to reveal intercellular and intracellular signaling relationships.

Methodology:

scSeqComm leverages scRNA-seq data to infer signaling pathways by analyzing gene expression levels associated with both intercellular and intracellular signals.