Exploring transcription modalities from bimodal, single-cell RNA sequencing data.

ABSTRACT: There is a growing interest in generating bimodal, single-cell RNA sequencing (RNA-seq) data for studying biological pathways. These data are predominantly utilized in understanding phenotypic trajectories using RNA velocities; however, the shape information encoded in the two-dimensional resolution of such data is not yet exploited. In this paper, we present an elliptical parametrization of two-dimensional RNA-seq data, from which we derived statistics that reveal four different modalities. These modalities can be interpreted as manifestations of the changes in the rates of splicing, transcription or degradation. We performed our analysis on a cell cycle and a colorectal cancer dataset. In both datasets, we found genes that are not picked up by differential gene expression analysis (DGEA)

SUBMITTER: Regenyi E 

PROVIDER: S-EPMC11655292 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature