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- Publisher Website: 10.1186/s13059-021-02461-5
- Scopus: eid_2-s2.0-85113687831
- PMID: 34452629
- WOS: WOS:000690963600001
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Article: BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
Title | BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments |
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Authors | |
Keywords | Single-cell RNA-seq Differential alternative splicing Differential momentum genes Variational Bayes |
Issue Date | 2021 |
Publisher | BioMed Central Ltd. The Journal's web site is located at http://www.genomebiology.com |
Citation | Genome Biology, 2021, v. 22, article no. 251 How to Cite? |
Abstract | RNA splicing is an important driver of heterogeneity in single cells through the expression of alternative transcripts and as a determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. BRIE2 is a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential disease-associated alternative splicing events and allows a principled selection of genes that capture heterogeneity in transcriptional kinetics and improve RNA velocity analyses, enabling the identification of splicing phenotypes associated with biological changes. |
Persistent Identifier | http://hdl.handle.net/10722/304898 |
ISSN | 2012 Impact Factor: 10.288 2023 SCImago Journal Rankings: 7.197 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Huang, Y | - |
dc.contributor.author | Sanguinetti, G | - |
dc.date.accessioned | 2021-10-05T02:36:47Z | - |
dc.date.available | 2021-10-05T02:36:47Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Genome Biology, 2021, v. 22, article no. 251 | - |
dc.identifier.issn | 1474-7596 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304898 | - |
dc.description.abstract | RNA splicing is an important driver of heterogeneity in single cells through the expression of alternative transcripts and as a determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. BRIE2 is a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential disease-associated alternative splicing events and allows a principled selection of genes that capture heterogeneity in transcriptional kinetics and improve RNA velocity analyses, enabling the identification of splicing phenotypes associated with biological changes. | - |
dc.language | eng | - |
dc.publisher | BioMed Central Ltd. The Journal's web site is located at http://www.genomebiology.com | - |
dc.relation.ispartof | Genome Biology | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Single-cell RNA-seq | - |
dc.subject | Differential alternative splicing | - |
dc.subject | Differential momentum genes | - |
dc.subject | Variational Bayes | - |
dc.title | BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments | - |
dc.type | Article | - |
dc.identifier.email | Huang, Y: yuanhua@hku.hk | - |
dc.identifier.authority | Huang, Y=rp02649 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1186/s13059-021-02461-5 | - |
dc.identifier.pmid | 34452629 | - |
dc.identifier.pmcid | PMC8393734 | - |
dc.identifier.scopus | eid_2-s2.0-85113687831 | - |
dc.identifier.hkuros | 325780 | - |
dc.identifier.volume | 22 | - |
dc.identifier.spage | article no. 251 | - |
dc.identifier.epage | article no. 251 | - |
dc.identifier.isi | WOS:000690963600001 | - |
dc.publisher.place | United Kingdom | - |