Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis.

ABSTRACT: Cellular heterogeneity in gene expression is driven by cellular processes, such as cell cycle and cell-type identity, and cellular environment such as spatial location. The cell cycle, in particular, is thought to be a key driver of cell-to-cell heterogeneity in gene expression, even in otherwise homogeneous cell populations. Recent advances in single-cell RNA-sequencing (scRNA-seq) facilitate detailed characterization of gene expression heterogeneity and can thus shed new light on the processes driving heterogeneity. Here, we combined fluorescence imaging with scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem cells (iPSCs). By using these data, we developed a novel approach to characterize cell cycle progression. Although standard methods a

SUBMITTER: Hsiao CJ 

PROVIDER: S-EPMC7197478 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature