Cell-type-specific co-expression inference from single cell RNA-sequencing data.

ABSTRACT: The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring c

SUBMITTER: Su C 

PROVIDER: S-EPMC9774209 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature