ArticleGenome biology2025
spVelo: RNA velocity inference for multi-batch spatial transcriptomics data.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comprehensive benchmarking of RNA velocity methods across single-cell datasets.Genome biology · 2026Article
- A dependency-aware deep generative model for inferring RNA velocity from spatial transcriptomics.Bioinformatics (Oxford, England) · 2026Article
- STEER: decoupling kinetics with Spatial-Temporal Explainable Expert model for RNA velocity inference.National science review · 2026Article
- RNAPaceDB: a dedicated database to dissect RNA velocity across diverse cell types.Nucleic acids research · 2026Article
- Spatiotemporal Atlas of Heart Development Reveals Blood-Flow-Dependent Cellular, Structural, Metabolic, and Spatial Remodeling.bioRxiv : the preprint server for biology · 2025Article
- spVelo: RNA velocity inference for multi-batch spatial transcriptomics data.Genome biology · 2025Article
- KSRV: a Kernel PCA-Based framework for inferring spatial RNA velocity at single-cell resolution.Frontiers in genetics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
RNA velocity has emerged as a powerful tool to interpret transcriptional dynamics and infer trajectory from snapshot datasets. However, current methods fail to utilize the spatial information inherent in spatial transcriptomics and lack scalability in multi-batch datasets. Here, we introduce spVelo, a scalable framework for RNA velocity inference of multi-batch spatial transcriptomics data. spVelo supports several downstream applications, including uncertainty quantification, complex trajectory pattern discovery, driver marker identification, gene regulatory network inference, and temporal cell-cell communication inference. spVelo has the potential to provide deeper insights into complex tissue organization and underscore biological mechanisms based on spatially resolved patterns.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.