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Massively parallel single-nucleus RNA-seq with DroNc-seq

By Inbal Avraham-Davidi, Anindita Basu, Tyler Burks, Karthik Shekhar, Matan Hofree, François Aguet, Ellen Gelfand, Kristin Ardlie, David A Weitz, Orit Rozenblatt-Rosen, Feng Zhang, Naomi Habib, Sourav Choudhury and Aviv Regev

Abstract

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 sequencin

Publisher: 'Springer Science and Business Media LLC'
Year: 2017
DOI identifier: 10.1038/nmeth.4407
OAI identifier: oai:dspace.mit.edu:1721.1/114253
Provided by: DSpace@MIT
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