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Alignment of single-cell trajectory trees with CAPITAL

Author

Listed:
  • Reiichi Sugihara

    (Osaka University)

  • Yuki Kato

    (Osaka University
    Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University)

  • Tomoya Mori

    (Bioinformatics Center, Institute for Chemical Research, Kyoto University)

  • Yukio Kawahara

    (Osaka University
    Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University)

Abstract

Global alignment of complex pseudotime trajectories between different single-cell RNA-seq datasets is challenging, as existing tools mainly focus on linear alignment of single-cell trajectories. Here we present CAPITAL (comparative analysis of pseudotime trajectory inference with tree alignment), a method for comparing single-cell trajectories with tree alignment whereby branching trajectories can be automatically compared. Computational tests on synthetic datasets and authentic bone marrow cells datasets indicate that CAPITAL has achieved accurate and robust alignments of trajectory trees, revealing various gene expression dynamics including gene–gene correlation conservation between different species.

Suggested Citation

  • Reiichi Sugihara & Yuki Kato & Tomoya Mori & Yukio Kawahara, 2022. "Alignment of single-cell trajectory trees with CAPITAL," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33681-3
    DOI: 10.1038/s41467-022-33681-3
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    References listed on IDEAS

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    1. Edroaldo Lummertz da Rocha & R. Grant Rowe & Vanessa Lundin & Mohan Malleshaiah & Deepak Kumar Jha & Carlos R. Rambo & Hu Li & Trista E. North & James J. Collins & George Q. Daley, 2018. "Reconstruction of complex single-cell trajectories using CellRouter," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    2. Yingyao Zhou & Bin Zhou & Lars Pache & Max Chang & Alireza Hadj Khodabakhshi & Olga Tanaseichuk & Christopher Benner & Sumit K. Chanda, 2019. "Metascape provides a biologist-oriented resource for the analysis of systems-level datasets," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    3. Robrecht Cannoodt & Wouter Saelens & Louise Deconinck & Yvan Saeys, 2021. "Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
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    Cited by:

    1. Jolene S. Ranek & Wayne Stallaert & J. Justin Milner & Margaret Redick & Samuel C. Wolff & Adriana S. Beltran & Natalie Stanley & Jeremy E. Purvis, 2024. "DELVE: feature selection for preserving biological trajectories in single-cell data," Nature Communications, Nature, vol. 15(1), pages 1-26, December.

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