scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

Abstract

Single-cell RNA-Seq suffers from heterogeneity in sequencing sparsity and complex differential patterns in gene expression. Here, the authors introduce a graph neural network based on a hypothesis-free deep learning framework as an effective representation of gene expression and cell–cell relationships.