DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics

Abstract Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes...

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Main Authors: Haotian Cui, Hassaan Maan, Maria C. Vladoiu, Jiao Zhang, Michael D. Taylor, Bo Wang
Format: Article
Language:English
Published: BMC 2024-01-01
Series:Genome Biology
Subjects:
Online Access:https://doi.org/10.1186/s13059-023-03148-9
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author Haotian Cui
Hassaan Maan
Maria C. Vladoiu
Jiao Zhang
Michael D. Taylor
Bo Wang
author_facet Haotian Cui
Hassaan Maan
Maria C. Vladoiu
Jiao Zhang
Michael D. Taylor
Bo Wang
author_sort Haotian Cui
collection DOAJ
description Abstract Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing RNA velocity to cell populations containing time-dependent kinetics and multiple lineages. DeepVelo infers time-varying cellular rates of transcription, splicing, and degradation, recovers each cell’s stage in the differentiation process, and detects functionally relevant driver genes regulating these processes. Application to various developmental and pathogenic processes demonstrates DeepVelo’s capacity to study complex differentiation and lineage decision events in heterogeneous scRNA-seq data.
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spelling doaj.art-6cf53315e61f4c3ea3e7ec45154ee2dc2024-01-21T12:23:36ZengBMCGenome Biology1474-760X2024-01-0125113110.1186/s13059-023-03148-9DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kineticsHaotian Cui0Hassaan Maan1Maria C. Vladoiu2Jiao Zhang3Michael D. Taylor4Bo Wang5Peter Munk Cardiac Center, University Health NetworkPeter Munk Cardiac Center, University Health NetworkDepartment of Pathology and Molecular Medicine, McMaster UniversityThe Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick ChildrenThe Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick ChildrenPeter Munk Cardiac Center, University Health NetworkAbstract Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing RNA velocity to cell populations containing time-dependent kinetics and multiple lineages. DeepVelo infers time-varying cellular rates of transcription, splicing, and degradation, recovers each cell’s stage in the differentiation process, and detects functionally relevant driver genes regulating these processes. Application to various developmental and pathogenic processes demonstrates DeepVelo’s capacity to study complex differentiation and lineage decision events in heterogeneous scRNA-seq data.https://doi.org/10.1186/s13059-023-03148-9RNA velocitySingle-cell RNA sequencingDeep LearningDevelopmentCancer
spellingShingle Haotian Cui
Hassaan Maan
Maria C. Vladoiu
Jiao Zhang
Michael D. Taylor
Bo Wang
DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
Genome Biology
RNA velocity
Single-cell RNA sequencing
Deep Learning
Development
Cancer
title DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
title_full DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
title_fullStr DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
title_full_unstemmed DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
title_short DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
title_sort deepvelo deep learning extends rna velocity to multi lineage systems with cell specific kinetics
topic RNA velocity
Single-cell RNA sequencing
Deep Learning
Development
Cancer
url https://doi.org/10.1186/s13059-023-03148-9
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