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Nature methods
Jun, 2024;21 (6): 1053-1062.

Spatial transition tensor of single cells.

Peijie Zhou, Federico Bocci, Tiejun Li, Qing Nie
Author Information
  1. Peijie Zhou: Department of Mathematics, University of California, Irvine, Irvine, CA, USA. ORCID
  2. Federico Bocci: Department of Mathematics, University of California, Irvine, Irvine, CA, USA.
  3. Tiejun Li: LMAM and School of Mathematical Sciences, Peking University, Beijing, China.
  4. Qing Nie: Department of Mathematics, University of California, Irvine, Irvine, CA, USA. qnie@uci.edu. ORCID
PMID: 38755322 DOI: 10.1038/s41592-024-02266-x

Abstract

Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics associated with multiple cell states and transition paths. Here we present spatial transition tensor (STT), a method that uses messenger RNA splicing and spatial transcriptomes through a multiscale dynamical model to characterize multistability in space. By learning a four-dimensional transition tensor and spatial-constrained random walk, STT reconstructs cell-state-specific dynamics and spatial state transitions via both short-time local tensor streamlines between cells and long-time transition paths among attractors. Benchmarking and applications of STT on several transcriptome datasets via multiple technologies on epithelial-mesenchymal transitions, blood development, spatially resolved mouse brain and chicken heart development, indicate STT's capability in recovering cell-state-specific dynamics and their associated genes not seen using existing methods. Overall, STT provides a consistent multiscale description of single-cell transcriptome data across multiple spatiotemporal scales.

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Grants

  1. R01 AR079150/NIAMS NIH HHS
  2. R01AR079150/Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
  3. U01 AR073159/NIAMS NIH HHS
  4. MCB2028424/National Science Foundation (NSF)
  5. U01AR073159/Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)

MeSH Term

Animals
Single-Cell Analysis
Mice
Transcriptome
RNA Splicing
Brain
Epithelial-Mesenchymal Transition
Gene Expression Profiling
Chickens
RNA, Messenger
Algorithms

Chemicals

RNA, Messenger
Journal Article
Article has an altmetric score of 25

Word Cloud

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