rCom: a route-based framework inferring cell type communication and regulatory network using single cell data

With recent advances of single cell RNA (scRNA) sequencing technology, several methods have been proposed to infer cell-cell communication by analyzing ligand-receptor pairs. However, existing methods have limited ways of using what we call "prior knowledge", i.e., what are already known (albeit incompletely) about the upstream for the ligand and the downstream for the receptor. In this paper, we present a novel framework, called rCom, capable of inferring cell-cell interactions by considering portions of pathways that would be associated with upstream of the ligand and downstream of receptors under examination. The rCom framework integrates knowledge from multiple biological databases including transcription factor-target database, ligand-receptor database and publicly available curated signaling pathway databases. We combine both algorithmic methods and heuristic rules to score how each putative ligand-receptor pair may matchup between all possible cell subtype pairs. Permutation test is performed to rank the hypothesized cell-cell communication routes. We performed a case study using single cell transcriptomic data from bone biology. Our literature survey suggests that rCom could be effective in discovering novel cell-cell communication relationships that have been only partially known in the field.