核糖核酸
巨量平行
单细胞分析
溶解
计算生物学
细胞
RNA序列
计算机科学
生物
大规模并行测序
化学
细胞生物学
转录组
分子生物学
基因表达
基因
基因组
遗传学
并行计算
作者
Todd M. Gierahn,Marc H. Wadsworth,Travis Hughes,Bryan Bryson,Andrew Butler,Rahul Satija,Sarah M. Fortune,J. Christopher Love,Alex K. Shalek
出处
期刊:Nature Methods
[Springer Nature]
日期:2017-02-13
卷期号:14 (4): 395-398
被引量:772
摘要
Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.
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