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

TitleSierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data
Authors
KeywordsscRNA-seq
Alternative polyadenylation
mRNA isoforms
Differential transcript use
Issue Date2020
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.genomebiology.com
Citation
Genome Biology, 2020, v. 21 How to Cite?
AbstractHigh-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.
Persistent Identifierhttp://hdl.handle.net/10722/284000
ISSN
2012 Impact Factor: 10.288
2023 SCImago Journal Rankings: 7.197
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPatrick, R-
dc.contributor.authorHumphreys, DT-
dc.contributor.authorJanbandhu, V-
dc.contributor.authorOshlack, A-
dc.contributor.authorHo, JWK-
dc.contributor.authorHarvey, RP-
dc.contributor.authorLo, KK-
dc.date.accessioned2020-07-20T05:55:13Z-
dc.date.available2020-07-20T05:55:13Z-
dc.date.issued2020-
dc.identifier.citationGenome Biology, 2020, v. 21-
dc.identifier.issn1474-7596-
dc.identifier.urihttp://hdl.handle.net/10722/284000-
dc.description.abstractHigh-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.-
dc.languageeng-
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.genomebiology.com-
dc.relation.ispartofGenome Biology-
dc.rightsGenome Biology. Copyright © BioMed Central Ltd.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectscRNA-seq-
dc.subjectAlternative polyadenylation-
dc.subjectmRNA isoforms-
dc.subjectDifferential transcript use-
dc.titleSierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data-
dc.typeArticle-
dc.identifier.emailHo, JWK: jwkho@hku.hk-
dc.identifier.authorityHo, JWK=rp02436-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s13059-020-02071-7-
dc.identifier.pmid32641141-
dc.identifier.pmcidPMC7341584-
dc.identifier.scopuseid_2-s2.0-85087727921-
dc.identifier.hkuros311051-
dc.identifier.volume21-
dc.identifier.isiWOS:000551797100001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1474-7596-

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