Massively parallel single-nucleus RNA-seq with DroNc-seq
Author(s)
Avraham-Davidi, Inbal; Burks, Tyler; Shekhar, Karthik; Hofree, Matan; Aguet, François; Gelfand, Ellen; Ardlie, Kristin; Weitz, David A; Rozenblatt-Rosen, Orit; Zhang, Feng; Habib, Naomi; Choudhury, Sourav; Regev, Aviv; Basu, Anindita, 1978-; ... Show more Show less
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Show full item recordAbstract
Single-nucleus RNA sequencing (sNuc-seq) profiles RNA from tissues that are preserved or cannot be dissociated, but it does not provide high throughput. Here, we develop DroNc-seq: massively parallel sNuc-seq with droplet technology. We profile 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient, and unbiased classification of cell types, paving the way for systematic charting of cell atlases. Keywords: Cellular neuroscience; Gene expression; Gene expression analysis; RNA sequencing
Date issued
2017-08Department
Massachusetts Institute of Technology. Department of Biology; Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; McGovern Institute for Brain Research at MIT; Koch Institute for Integrative Cancer Research at MITJournal
Nature Methods
Publisher
Nature Publishing Group
Citation
Habib, Naomi et al. “Massively Parallel Single-Nucleus RNA-Seq with DroNc-Seq.” Nature Methods 14, 10 (August 2017): 955–958 © 2017 Nature America
Version: Author's final manuscript
ISSN
1548-7091
1548-7105