CellCom2: An Integrated Web Platform for Flexible Prediction and Visualization Analysis of Cell-cell Communication

Cell-cell communication across diverse cell types and tissues underlies proper organismal function and is primarily mediated by interactions between secreted ligands and cell-surface receptors. Understanding these molecular interactions is essential for elucidating regulatory networks governing physiological and pathological processes and for identifying potential therapeutic targets. Although several computational tools have been developed for inferring intercellular communication, many existing methods require substantial programming expertise, rely on restricted or method-specific biological resources, and provide limited result visualization. To overcome these limitations, we developed CellCom2, an upgraded version of CellCom, a user-friendly web platform for the prediction and visualization analysis of ligand-receptor-mediated intercellular communication. CellCom2 integrates a comprehensive collection of prior biological knowledge, including ligand-receptor, receptor-transcription factor, and transcription factor-target gene interactions, together with a suite of state-of-the-art prediction algorithms. The platform allows flexible, user-defined combinations of biological resources and computational methods to accommodate diverse analysis scenarios. To reconcile results from different methods, CellCom2 implements a principled consensus integration strategy that assigns adaptive weights to quantify inter-method agreement and produce robust communication scores. In addition, CellCom2 provides systematic and multiscale visualization to facilitate the interpretation of intercellular communication patterns. Validation on multiple scRNA-seq and spatial transcriptomics datasets demonstrates that CellCom2 enhances the reliability, interpretability, and reproducibility of intercellular communication inference.