Patrick, Ralph and Humphreys, David T. and Janbandhu, Vaibhao and Oshlack, Alicia and Ho, Joshua W.K. and Harvey, Richard P. and Lo, Kitty K. (2020) Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data. Genome Biology, 21 (1). p. 167. ISSN 1474-760X
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Sierra-Discovery-of-differential-transcript-usage-from-polyAcaptured-singlecell-RNAseq-dataGenome-Biology.pdf Available under License Creative Commons Attribution No Derivatives. Download (3MB) | Preview |
Abstract
High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall expression levels, largely ignoring alternative mRNA isoform expression. We present a computational pipeline, Sierra, that readily detects differential transcript usage from data generated by commonly used polyA-captured scRNA-seq technology. We validate Sierra by comparing cardiac scRNA-seq cell types to bulk RNA-seq of matched populations, finding significant overlap in differential transcripts. Sierra detects differential transcript usage across human peripheral blood mononuclear cells and the Tabula Muris, and 3 'UTR shortening in cardiac fibroblasts. Sierra is available at https://github.com/VCCRI/Sierra .
| Item Type: | Article |
|---|---|
| Subjects: | R Medicine > R Medicine (General) |
| Depositing User: | Repository Administrator |
| Date Deposited: | 21 Jul 2020 22:32 |
| Last Modified: | 19 Oct 2021 00:32 |
| URI: | http://eprints.victorchang.edu.au/id/eprint/1009 |
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