NonLoss: a novel analytical method for differential biological module identification from single-cell transcriptome.

ABSTRACT:

Background

The identification of disease-related biological modules plays an important role in our understanding of the process of diseases. Although single-cell RNA sequencing (scRNA-seq) provides high-resolution transcriptome data that can potentially characterize subtle gene expression changes within cells, the susceptibility of the gene expression information to the influence of individual genes also makes it difficult to distinguish the biological module.

Methods

To quantify gene expression information for biological function modules, we adopted the method based on Shannon's entropy and Spearman rank correlation analysis. The ingenious combination of these two methods enables the variation analysis of the former and the consistency analysis of the latter to make a more

SUBMITTER: Zhao H 

PROVIDER: S-EPMC8756206 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature