工具箱
核糖核酸
小核RNA
生物
细胞
计算生物学
核心
单细胞分析
RNA序列
细胞生物学
转录组
计算机科学
基因表达
遗传学
基因
非编码RNA
程序设计语言
作者
Michal Slyper,Caroline Porter,Orr Ashenberg,Julia Waldman,Eugene Drokhlyansky,Isaac Wakiro,Christopher S. Smillie,Gabriela Smith-Rosario,Jingyi Wu,Danielle Dionne,Sébastien Vigneau,Judit Jané‐Valbuena,Timothy L. Tickle,Sara Napolitano,Mei-Ju Su,Anand G. Patel,Åsa Karlström,Simon Gritsch,Masashi Nomura,Avinash Waghray
出处
期刊:Nature Medicine
[Nature Portfolio]
日期:2020-05-01
卷期号:26 (5): 792-802
被引量:597
标识
DOI:10.1038/s41591-020-0844-1
摘要
Abstract Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.
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