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Obstacles to detecting isoforms using full-length scRNA-seq data by Jennifer Westoby; Pavel Artemov; Martin Hemberg; Anne Ferguson-Smith is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Obstacles to detecting isoforms using full-length scRNA-seq data about?

## Background Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses. ## Results In this study, we take a simulation based approach in which we explicitly account for dropouts and isoform quantification errors. We use our simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, we ask what limitations must be overcome to make splicing analysis feasible. We find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing. In mice and other well-established model organisms, the relatively low rate of isoform quantification errors poses a lesser obstacle to splicing analysis. We find that different models of isoform choice meaningfully change our simulation results. ## Conclusions To accurately study alternative splicing with single-cell RNA-seq, a better und

Who reads Obstacles to detecting isoforms using full-length scRNA-seq data?

Author

Jennifer Westoby; Pavel Artemov; Martin Hemberg; Anne Ferguson-Smith

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central Ltd, 2001-; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc.; Research Square (ISSN 1465-6906)

Published

2020

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)