Skip to main navigation Skip to search Skip to main content

spVelo: RNA velocity inference for multi-batch spatial transcriptomics data

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number239
JournalGenome biology
Volume26
Issue number1
DOIs
StatePublished - Dec 2025

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

Fingerprint

Dive into the research topics of 'spVelo: RNA velocity inference for multi-batch spatial transcriptomics data'. Together they form a unique fingerprint.

Cite this