核心
巨量平行
RNA序列
大规模并行测序
核糖核酸
生物
计算生物学
计算机科学
细胞生物学
转录组
基因
遗传学
基因表达
并行计算
DNA测序
作者
Naomi Habib,Inbal Avraham‐Davidi,Anindita Basu,Tyler Burks,Karthik Shekhar,Matan Hofree,Sourav Choudhury,François Aguet,Ellen Gelfand,Kristin Ardlie,David A. Weitz,Orit Rozenblatt–Rosen,Feng Zhang,Aviv Regev
出处
期刊:Nature Methods
[Springer Nature]
日期:2017-08-28
卷期号:14 (10): 955-958
被引量:978
摘要
DroNc-seq enables low-cost, high-throughput single-nucleus RNA-seq of tissues that are archived or difficult to dissociate, such as post-mortem human brain. 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.
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