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Reconstruction of complex single-cell trajectories using CellRouter

Author

Listed:
  • Edroaldo Lummertz da Rocha

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Medical School
    Harvard Stem Cell Institute
    Manton Center for Orphan Disease Research)

  • R. Grant Rowe

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Medical School
    Harvard Stem Cell Institute
    Manton Center for Orphan Disease Research)

  • Vanessa Lundin

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Medical School
    Harvard Stem Cell Institute
    Manton Center for Orphan Disease Research)

  • Mohan Malleshaiah

    (Harvard Medical School
    110 Avenue Des Pins Ouest)

  • Deepak Kumar Jha

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Medical School
    Harvard Stem Cell Institute
    Manton Center for Orphan Disease Research)

  • Carlos R. Rambo

    (Federal University of Santa Catarina)

  • Hu Li

    (Mayo Clinic)

  • Trista E. North

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Stem Cell Institute)

  • James J. Collins

    (Broad Institute of MIT and Harvard
    Harvard University)

  • George Q. Daley

    (Boston Children’s Hospital and Dana-Farber Cancer Institute
    Harvard Medical School
    Harvard Stem Cell Institute
    Manton Center for Orphan Disease Research)

Abstract

A better understanding of the cell-fate transitions that occur in complex cellular ecosystems in normal development and disease could inform cell engineering efforts and lead to improved therapies. However, a major challenge is to simultaneously identify new cell states, and their transitions, to elucidate the gene expression dynamics governing cell-type diversification. Here, we present CellRouter, a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data. We demonstrate its versatility by applying CellRouter to single-cell RNA sequencing data sets to reconstruct cell-state transition trajectories during hematopoietic stem and progenitor cell (HSPC) differentiation to the erythroid, myeloid and lymphoid lineages, as well as during re-specification of cell identity by cellular reprogramming of monocytes and B-cells to HSPCs. CellRouter opens previously undescribed paths for in-depth characterization of complex cellular ecosystems and establishment of enhanced cell engineering approaches.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03214-y
    DOI: 10.1038/s41467-018-03214-y
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    Cited by:

    1. 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.
    2. Peizhuo Wang & Xiao Wen & Han Li & Peng Lang & Shuya Li & Yipin Lei & Hantao Shu & Lin Gao & Dan Zhao & Jianyang Zeng, 2023. "Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Chieh Lin & Jun Ding & Ziv Bar-Joseph, 2020. "Inferring TF activation order in time series scRNA-Seq studies," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-19, February.

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