Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data

Genome Biology

Alicia Oshlack¹  Kitty K. Lo²  Vaibhao Janbandhu³  David T. Humphreys³  Richard P. Harvey³  Joshua W.K. Ho³  Ralph Patrick³ 

[1] Murdoch Children’s Research Institute;School of Mathematics and Statistics, Faculty of Science, The University of Sydney;Victor Chang Cardiac Research Institute;

关键词: scRNA-seq;    Alternative polyadenylation;    mRNA isoforms;    Differential transcript use;   

DOI  :  10.1186/s13059-020-02071-7

来源: DOAJ

【 摘 要 】

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 .

【 授权许可】

Unknown