title: Robust detection of alternative splicing in a population of single cells.
abstract: Single cell RNA-seq experiments provide valuable insight into cellular heterogeneity but suffer from low coverage, 3' bias and technical noise. These unique properties of single cell RNA-seq data make study of alternative splicing difficult, and thus most single cell studies have restricted analysis of transcriptome variation to the gene level. To address these limitations, we developed SingleSplice, which uses a statistical model to detect genes whose isoform usage shows biological variation significantly exceeding technical noise in a population of single cells. Importantly, SingleSplice is tailored to the unique demands of single cell analysis, detecting isoform usage differences without attempting to infer expression levels for full-length transcripts. Using data from spike-in transcripts, we found that our approach detects variation in isoform usage among single cells with high sensitivity and specificity. We also applied SingleSplice to data from mouse embryonic stem cells and discovered a set of genes that show significant biological variation in isoform usage across the set of cells. A subset of these isoform differences are linked to cell cycle stage, suggesting a novel connection between alternative splicing and the cell cycle.
authors.affiliation: Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599-3175, USA Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599-7264, USA.
authors.forename: Joshua D
authors.initials: JD
authors.lastname: Welch
authors.affiliation: Computational Oncology, Sage Bionetworks, 1100 Fairview Ave. N., Seattle, WA 98109, USA.
authors.forename: Yin
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599-3175, USA Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599-7264, USA prins@cs.unc.edu.
authors.forename: Jan F
authors.initials: JF
authors.lastname: Prins
mesh_terms: D017398:Alternative Splicing / Q000235:genetics*; D000818:Animals; D001483:Base Sequence; D002453:Cell Cycle / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D053595:Embryonic Stem Cells / Q000166:cytology*; D020869:Gene Expression Profiling / Q000379:methods; D051379:Mice; D015233:Models, Statistical; D020033:Protein Isoforms / Q000235:genetics*; D012313:RNA / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D020033:Protein Isoforms; D012313:RNA