BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments

BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments

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 e...

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Main Authors: Yuanhua Huang, Guido Sanguinetti
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Genome Biology
Subjects:
Single-cell RNA-seq
Differential alternative splicing
Differential momentum genes
Variational Bayes
Online Access:https://doi.org/10.1186/s13059-021-02461-5
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spelling doaj-45f339cf4e3e400badb35bf13b3b6dde2021-08-29T11:45:20ZengBMCGenome Biology1474-760X2021-08-0122111510.1186/s13059-021-02461-5BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experimentsYuanhua Huang0Guido Sanguinetti1School of Biomedical Sciences, University of Hong KongSchool of Informatics, University of EdinburghAbstract 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.https://doi.org/10.1186/s13059-021-02461-5Single-cell RNA-seqDifferential alternative splicingDifferential momentum genesVariational Bayes
collection DOAJ
language English
format Article
sources DOAJ
author Yuanhua Huang
Guido Sanguinetti
spellingShingle Yuanhua Huang
Guido Sanguinetti
BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
Genome Biology
Single-cell RNA-seq
Differential alternative splicing
Differential momentum genes
Variational Bayes
author_facet Yuanhua Huang
Guido Sanguinetti
author_sort Yuanhua Huang
title BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
title_short BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
title_full BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
title_fullStr BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
title_full_unstemmed BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
title_sort brie2: computational identification of splicing phenotypes from single-cell transcriptomic experiments
publisher BMC
series Genome Biology
issn 1474-760X
publishDate 2021-08-01
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.
topic Single-cell RNA-seq
Differential alternative splicing
Differential momentum genes
Variational Bayes
url https://doi.org/10.1186/s13059-021-02461-5
work_keys_str_mv AT yuanhuahuang brie2computationalidentificationofsplicingphenotypesfromsinglecelltranscriptomicexperiments
AT guidosanguinetti brie2computationalidentificationofsplicingphenotypesfromsinglecelltranscriptomicexperiments
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