Massively parallel digital transcriptional profiling of single cells

Massively parallel digital transcriptional profiling of single cells

Single-cell gene expression analysis is challenging. This work describes a new droplet-based single cell RNA-seq platform capable of processing tens of thousands of cells across 8 independent samples in minutes, and demonstrates cellular subtypes and host–donor chimerism in transplant patients.

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Auteurs principaux: 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, Joe Shuga, Luz Montesclaros, Jason G. Underwood, Donald A. Masquelier, Stefanie Y. Nishimura, Michael Schnall-Levin, Paul W. Wyatt, Christopher M. Hindson, Rajiv Bharadwaj, Alexander Wong, Kevin D. Ness, Lan W. Beppu, H. Joachim Deeg, Christopher McFarland, Keith R. Loeb, William J. Valente, Nolan G. Ericson, Emily A. Stevens, Jerald P. Radich, Tarjei S. Mikkelsen, Benjamin J. Hindson, Jason H. Bielas
Format: article
Langue:EN
Publié: Nature Portfolio 2017
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Science
Q
Accès en ligne:https://doaj.org/article/9c33171e807745c7908a1e1e9a3712e3
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Résumé:Single-cell gene expression analysis is challenging. This work describes a new droplet-based single cell RNA-seq platform capable of processing tens of thousands of cells across 8 independent samples in minutes, and demonstrates cellular subtypes and host–donor chimerism in transplant patients.

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