TY - JOUR
T1 - Massively parallel single-nucleus RNA-seq with DroNc-seq
AU - Habib, Naomi
AU - Avraham-Davidi, Inbal
AU - Basu, Anindita
AU - Burks, Tyler
AU - Shekhar, Karthik
AU - Hofree, Matan
AU - Choudhury, Sourav R.
AU - Aguet, François
AU - Gelfand, Ellen
AU - Ardlie, Kristin
AU - Weitz, David A.
AU - Rozenblatt-Rosen, Orit
AU - Zhang, Feng
AU - Regev, Aviv
N1 - Publisher Copyright:
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85031046570&partnerID=8YFLogxK
U2 - 10.1038/nmeth.4407
DO - 10.1038/nmeth.4407
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C2 - 28846088
AN - SCOPUS:85031046570
SN - 1548-7091
VL - 14
SP - 955
EP - 958
JO - Nature Methods
JF - Nature Methods
IS - 10
ER -
