biostudies-literatureUnknown34(14)Vu TNSERCSwedish Cancer SocietySwedish e-Science Research CentreSwedish Research CouncilMotivation: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, Bioinformatics (Oxford, England)2392-2400https://www.ebi.ac.uk/biostudies/studies/S-EPMC6041805biostudies-literatureIsoform-level gene expression patterns in single-cell RNA-sequencing data.PMC6041805Pawitan YWills QFNiu NKalari KRVu TNRantalainen MWang LfalseIsoform-level gene expression patterns in single-cell RNA-sequencing data.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, 2018-01-01T00:00:00Z2018 Jul2025-04-04T18:41:33.421Z2019-03-26T23:46:39ZS-EPMC60418052949001510.1093/bioinformatics/bty100