|
Abstract:
|
Intercellular interactions (so called "Cell-Cell Communication"), mediated by ligand-receptor complexes, are important to many biological processes, including immune responses. The single-cell RNA sequencing (scRNA-seq) technologies allow the measurement of the gene expression of ligand and receptors. We develop a novel statistical method to identify differential intercellular ligand-receptor interactions from single-cell RNA sequencing data. Here, we firstly introduce a new connection scores to quantify the strength of ligand-receptor interactions between two cell types, by accounting the excess zeros in the scRNAseq data distribution. We then fit a two-component generalized linear mixed model to those scores. We applied this method to the scRNAseq data of humanized mouse spleen samples with or without the infection of acute human immunodeficiency virus (HIV) to assess the HIV infection effects on the ligand-receptor interactions and understand cell-cell communications among cell types.
|
