scENT for Revealing Gene Clusters From Single-Cell RNA-Seq Data.

Recently, the fast development of single-cell RNA-seq (scRNA-seq) techniques has enabled high-resolution transcriptomic statistical analysis of individual cells in heterogeneous tissues, which can help researchers to explore the relationship between genes and human diseases. The emerging scRNA-seq data results in new analysis methods aiming to identify cell-level clustering and annotations. However, there are few methods developed to gain insights into the gene-level clusters with biological significance.