Isoform-level gene expression patterns in single-cell RNA-sequencing data.

ABSTRACT: Motivation:RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. Results:We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line,

SUBMITTER: Vu TN 

PROVIDER: S-EPMC6041805 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature