CellVocal Attributes Transcriptional Dynamics to Spatial Signalling

Understanding how local signalling shapes cell-state transitions requires linking spatial context to transcriptional dynamics. Here we present CellVocal, a framework that integrates spatial RNA velocity with cell-cell communication to decompose cell-state transitions into intrinsic and communication-associated components and further attribute their contributions to signalling modules and neighbouring sender cells. CellVocal recovered complex trajectories and communication perturbations in simulations and reconstructed coherent dynamics and spatially restricted ligand-receptor programmes across the mouse brain, gut and lung. Further analyses linked inferred NCAM1-NCAM1 signalling to lower cell-cycle-associated RNA velocity during embryonic neurogenesis. In melanoma, inferred local MIF-CD74+CD44 signalling corresponded to a predicted decline in the melanocytic programme. Analysis of acute liver failure identified hepatocyte-derived ANGPTL4-SDC1 signalling in association with acetaminophen-related communication enrichment and predicted matrix-remodelling RNA dynamics. By converting static ligand-receptor maps into velocity-constrained networks of signalling influence, CellVocal provides a general strategy for generating spatially resolved hypotheses about how intercellular communication contributes to predicted transcriptional changes.