Massively parallel digital transcriptional profiling of single cells

@article{Zheng2017MassivelyPD,
  title={Massively parallel digital transcriptional profiling of single cells},
  author={Grace X. Y. Zheng and Jessica M. Terry and P. Belgrader and Paul Ryvkin and Zachary W. Bent and Ryan Wilson and Solongo B. Ziraldo and T. Wheeler and Geoffrey P. McDermott and Junjie Zhu and M. Gregory and J. Shuga and Luz Montesclaros and J. Underwood and D. Masquelier and S. Nishimura and Michael Schnall-Levin and Paul W Wyatt and Christopher M. Hindson and R. Bharadwaj and Alexander Wong and K. Ness and L. Beppu and H. Deeg and C. McFarland and K. Loeb and W. Valente and N. Ericson and Emily A. Stevens and J. Radich and T. Mikkelsen and B. Hindson and J. Bielas},
  journal={Nature Communications},
  year={2017},
  volume={8}
}
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… Expand
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