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Massively parallel digital transcriptional profiling of single cells

Author

Listed:
  • Grace X. Y. Zheng

    (10x Genomics Inc.)

  • Jessica M. Terry

    (10x Genomics Inc.)

  • Phillip Belgrader

    (10x Genomics Inc.)

  • Paul Ryvkin

    (10x Genomics Inc.)

  • Zachary W. Bent

    (10x Genomics Inc.)

  • Ryan Wilson

    (10x Genomics Inc.)

  • Solongo B. Ziraldo

    (10x Genomics Inc.)

  • Tobias D. Wheeler

    (10x Genomics Inc.)

  • Geoff P. McDermott

    (10x Genomics Inc.)

  • Junjie Zhu

    (10x Genomics Inc.)

  • Mark T. Gregory

    (Translational Research Program, Fred Hutchinson Cancer Research Center)

  • Joe Shuga

    (10x Genomics Inc.)

  • Luz Montesclaros

    (10x Genomics Inc.)

  • Jason G. Underwood

    (10x Genomics Inc.
    University of Washington)

  • Donald A. Masquelier

    (10x Genomics Inc.)

  • Stefanie Y. Nishimura

    (10x Genomics Inc.)

  • Michael Schnall-Levin

    (10x Genomics Inc.)

  • Paul W. Wyatt

    (10x Genomics Inc.)

  • Christopher M. Hindson

    (10x Genomics Inc.)

  • Rajiv Bharadwaj

    (10x Genomics Inc.)

  • Alexander Wong

    (10x Genomics Inc.)

  • Kevin D. Ness

    (10x Genomics Inc.)

  • Lan W. Beppu

    (Fred Hutchinson Cancer Research Center)

  • H. Joachim Deeg

    (Fred Hutchinson Cancer Research Center)

  • Christopher McFarland

    (Seattle Cancer Care Alliance Clinical Immunogenetics Laboratory)

  • Keith R. Loeb

    (Fred Hutchinson Cancer Research Center
    University of Washington)

  • William J. Valente

    (Translational Research Program, Fred Hutchinson Cancer Research Center
    Medical Scientist Training Program, University of Washington School of Medicine
    Molecular and Cellular Biology Graduate Program, University of Washington)

  • Nolan G. Ericson

    (Translational Research Program, Fred Hutchinson Cancer Research Center)

  • Emily A. Stevens

    (Fred Hutchinson Cancer Research Center)

  • Jerald P. Radich

    (Fred Hutchinson Cancer Research Center)

  • Tarjei S. Mikkelsen

    (10x Genomics Inc.)

  • Benjamin J. Hindson

    (10x Genomics Inc.)

  • Jason H. Bielas

    (Translational Research Program, Fred Hutchinson Cancer Research Center
    University of Washington
    Molecular and Cellular Biology Graduate Program, University of Washington
    Fred Hutchinson Cancer Research Center)

Abstract

Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system’s technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system’s ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.

Suggested Citation

  • Grace X. Y. Zheng & Jessica M. Terry & Phillip Belgrader & Paul Ryvkin & Zachary W. Bent & Ryan Wilson & Solongo B. Ziraldo & Tobias D. Wheeler & Geoff P. McDermott & Junjie Zhu & Mark T. Gregory & Jo, 2017. "Massively parallel digital transcriptional profiling of single cells," Nature Communications, Nature, vol. 8(1), pages 1-12, April.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14049
    DOI: 10.1038/ncomms14049
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    Cited by:

    1. Qunlun Shen & Shihua Zhang, 2021. "Approximate distance correlation for selecting highly interrelated genes across datasets," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-18, November.
    2. Jinzhou Li & Marloes H. Maathuis, 2021. "GGM knockoff filter: False discovery rate control for Gaussian graphical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 534-558, July.
    3. Snehalika Lall & Sumanta Ray & Sanghamitra Bandyopadhyay, 2022. "A copula based topology preserving graph convolution network for clustering of single-cell RNA-seq data," PLOS Computational Biology, Public Library of Science, vol. 18(3), pages 1-16, March.
    4. Lin Lin & Wei Shi & Jianbo Ye & Jia Li, 2023. "Multisource single‐cell data integration by MAW barycenter for Gaussian mixture models," Biometrics, The International Biometric Society, vol. 79(2), pages 866-877, June.

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