Massively parallel digital transcriptional profiling of single cells

@inproceedings{Zheng2017MassivelyPD,
  title={Massively parallel digital transcriptional profiling of single cells},
  author={Grace X. Y. Zheng and Jessica M. Terry and Phillip Belgrader and Paul Ryvkin and Zachary W. Bent and Ryan Wilson and Solongo B. Ziraldo and Tobias D. Wheeler and Geoff P. McDermott and Junjie Zhu and Mark T. Gregory and Joe Shuga and Luz Montesclaros and Jason G. Underwood and Donald A. Masquelier and Stefanie Y. Nishimura and Michael Schnall-Levin and Paul W. Wyatt and Christopher M. Hindson and Rajiv Bharadwaj and Aloysius Wong and Kevin D. Ness and Lan W. Beppu and H Joachim Deeg and Christopher McFarland and Keith R. Loeb and W J Valente and Nolan G. Ericson and Emily A. Stevens and Jerald P Radich and Tarjei S. Mikkelsen and Benjamin J. Hindson and Jason H. Bielas},
  booktitle={Nature communications},
  year={2017}
}
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… CONTINUE READING
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