Uncovering hypergraphs of cell-cell interaction from single cell RNA-sequencing data

Abstract

AbstractComplex biological systems can be described as a multitude of cell-cell interactions (CCIs). Recent single-cell RNA-sequencing technologies have enabled the detection of CCIs and related ligand-receptor (L-R) gene expression simultaneously. However, previous data analysis methods have focused on only one-to-one CCIs between two cell types. To also detect many-to-many CCIs, we proposescTensor, a novel method for extracting representative triadic relationships (hypergraphs), which include (i) ligand-expression, (ii) receptor-expression, and (iii) L-R pairs. When applied to simulated and empirical datasets,scTensorwas able to detect some hypergraphs including paracrine/autocrine CCI patterns, which cannot be detected by previous methods.