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

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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Publication Details

Journal
Genome biology
Published
2025-08-11
DOI
https://doi.org/10.1186/s13059-025-03701-8
Citations
3
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
2.42

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article

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

Tianyu Liu, Hongyu Zhao, Wenxin Long, Lingzhou Xue
3 citations
Genome biology
Single-cell and spatial transcriptomics
2.42
article

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

Tianyu Liu, Hongyu Zhao, Wenxin Long, Lingzhou Xue
article en
3 citations

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.

Genome biologyVol. 26(1)
Pennsylvania State University (US), Yale University (US)
National Institutes of Health
Openalex Percentile: Top 11%
Single-cell and spatial transcriptomics
2.42
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