Cross-tissue gene expression interactions from bulk, single cell and spatial transcriptomics with crossWGCNA

Background: Understanding the molecular interactions between cells, tissues or organs is key to understanding the functioning of a biological system as a whole. Results: Here, we propose crossWGCNA: a co-expression-based method that identifies highly interacting genes unbiasedly and that we employ to study stroma-epithelium communication in breast cancer. CrossWGCNA can be applied to bulk, single cell and spatial transcriptomics data. We validate it both in silico and experimentally, and we provide a fully documented R package allowing users to employ it. Conclusions: The wide applicability and agnostic nature of our tool make it complementary to existing methods overcoming the limitations arising from strong baseline assumptions.