Journal article

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

Ralph Patrick, David Humphreys, Vaibhao Janbandhu, Alicia Oshlack, Joshua WK Ho, Richard Harvey, Kitty Lo

Published : 2019

Abstract

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 Tabul..

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