A Guide to Trajectory Inference and RNA Velocity.
Bioinformatics
Cell differentiation
Computational biology
Gene regulation
RNA velocity
Single-cell RNA sequencing
Splicing
Trajectory inference
Transcription
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2023
2023
Historique:
entrez:
10
12
2022
pubmed:
11
12
2022
medline:
15
12
2022
Statut:
ppublish
Résumé
Technological developments have led to an explosion of high-throughput single-cell data, which are revealing unprecedented perspectives on cell identity. Recently, significant attention has focused on investigating, from single-cell RNA-sequencing (scRNA-seq) data, cellular dynamic processes, such as cell differentiation, cell cycle and cell (de)activation. In particular, trajectory inference methods, by ordering cells along a trajectory, allow estimating a differentiation tree of cells. While trajectory inference tools typically work with gene expression levels, common scRNA-seq protocols allow the identification and quantification of unspliced pre-mRNAs and mature spliced mRNAs for each gene. By exploiting the abundance of unspliced and spliced mRNA, one can infer the RNA velocity of individual cells, i.e., the time derivative of the gene expression state of cells. Whereas traditional trajectory inference methods reconstruct cellular dynamics given a population of cells of varying maturity, RNA velocity relies on a dynamical model describing splicing dynamics. Here, we initially discuss conceptual and theoretical aspects of both approaches, then illustrate how they can be combined together, and finally present an example use case on real data.
Identifiants
pubmed: 36495456
doi: 10.1007/978-1-0716-2756-3_14
doi:
Substances chimiques
RNA
63231-63-0
RNA, Messenger
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
269-292Informations de copyright
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
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