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UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference

Author

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  • Mingze Gao

    (University of Hong Kong)

  • Chen Qiao

    (University of Hong Kong)

  • Yuanhua Huang

    (University of Hong Kong
    University of Hong Kong)

Abstract

The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches.

Suggested Citation

  • Mingze Gao & Chen Qiao & Yuanhua Huang, 2022. "UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34188-7
    DOI: 10.1038/s41467-022-34188-7
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    Cited by:

    1. Anneke Brümmer & Sven Bergmann, 2024. "Disentangling genetic effects on transcriptional and post-transcriptional gene regulation through integrating exon and intron expression QTLs," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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