talklr uncovers ligand-receptor mediated intercellular crosstalk

Abstract

Single cell RNA-seq measures the transcriptomes of many cell types across diverse conditions. However, an emerging challenge is to uncover how different cell types communicate with each other to maintain tissue homeostasis, and how inter-cellular communications are perturbed in diseases. To address this problem, we developed talklr, an information theory-based approach to uncover potential ligand-receptor interactions involved in tissue homeostasis and diseases. Compared to existing approaches that analyze changes in each gene in each cell type separately, talklr uses a holistic approach to simultaneously consider expression changes in both ligands and receptors across multiple cell types and conditions. talklr outperformed existing approaches in identifying ligand-receptor interactions, including those known to be important for tissue-specific functions and diseases across diverse datasets. talklr can reveal important signaling events in many biological problems in an unbiased way, and will be a valuable tool in single cell RNA-seq analysis. talklr is available as both an interactive website and an R package.