Methods for cell–cell communication inference, analysis and visualization.
(Left) Cell–cell communication inference requires at least two inputs. One is the expression profiles of signaling genes across cells or spots from single-cell transcriptomics or spatial transcriptomics and the other is the prior knowledge of ligand–receptor interactions from a curated database. Spatial location of each cell or spot can also be integrated with expression data for the inference. Example databases are listed at the bottom. (Middle) Computational tools of cell–cell communication inference and analysis can be grouped based on whether they incorporate spatial information, whether they consider the downstream response, or whether they are designed for comparison analysis across conditions. (Right) The inferred cell–cell communication can be visualized using different plots and mapped onto the tissue based on their spatial locations. Examples of cell–cell communication analysis from CellChat tool show that it can identify multicellular programs and perform comparison analysis across conditions.