Protocol to dissociate, process, and analyze the human lung tissue using single-cell RNA-seq.
Protocol to dissociate, process, and analyze the human lung tissue using single-cell RNA-seq.
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DOI:
10.1016/j.xpro.2022.101776
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发表时间:
2022-12-16
期刊:
影响因子:
--
通讯作者:
Mazutis L
中科院分区:
文献类型:
--
作者:
Quintanal-Villalonga Á;Chan JM;Masilionis I;Gao VR;Xie Y;Allaj V;Chow A;Poirier JT;Pe'er D;Rudin CM;Mazutis L
We report a protocol for obtaining high-quality single-cell transcriptomics data from human lung biospecimens acquired from core needle biopsies, fine-needle aspirates, surgical resection, and pleural effusions. The protocol relies upon the brief mechanical and enzymatic disruption of tissue, enrichment of live cells by fluorescence-activated cell sorting (FACS), and droplet-based single-cell RNA sequencing (scRNA-seq). The protocol also details a procedure for analyzing the scRNA-seq data. For complete details on the use and execution of this protocol, please refer to. Preparation of diverse human lung biospecimens for scRNA-seq Enrichment for live cells by FACS Applicable to different scRNA-seq platforms Computational workflow provides critical guideline for step-by-step data analysis Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. We report a protocol for obtaining high-quality single-cell transcriptomics data from human lung biospecimens acquired from core needle biopsies, fine-needle aspirates, surgical resection, and pleural effusions. The protocol relies upon the brief mechanical and enzymatic disruption of tissue, enrichment of live cells by fluorescence-activated cell sorting (FACS), and droplet-based single-cell RNA sequencing (scRNA-seq). The protocol also details a procedure for analyzing the scRNA-seq data.
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影响因子:
64.5
作者:
Levine JH;Simonds EF;Bendall SC;Davis KL;Amir el-AD;Tadmor MD;Litvin O;Fienberg HG;Jager A;Zunder ER;Finck R;Gedman AL;Radtke I;Downing JR;Pe'er D;Nolan GP
通讯作者:
Nolan GP
影响因子:
46.9
作者:
Greenwald, Noah F.;Miller, Geneva;Moen, Erick;Kong, Alex;Kagel, Adam;Dougherty, Thomas;Fullaway, Christine Camacho;McIntosh, Brianna J.;Leow, Ke Xuan;Schwartz, Morgan Sarah;Pavelchek, Cole;Cui, Sunny;Camplisson, Isabella;Bar-Tal, Omer;Singh, Jaiveer;Fong, Mara;Chaudhry, Gautam;Abraham, Zion;Moseley, Jackson;Warshawsky, Shiri;Soon, Erin;Greenbaum, Shirley;Risom, Tyler;Hollmann, Travis;Bendall, Sean C.;Keren, Leeat;Graf, William;Angelo, Michael;Van Valen, David
通讯作者:
Van Valen, David
影响因子:
64.5
作者:
van Dijk D;Sharma R;Nainys J;Yim K;Kathail P;Carr AJ;Burdziak C;Moon KR;Chaffer CL;Pattabiraman D;Bierie B;Mazutis L;Wolf G;Krishnaswamy S;Pe'er D
通讯作者:
Pe'er D
影响因子:
14.9
作者:
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者:
Smyth GK
影响因子:
16.6
作者:
Zheng GX;Terry JM;Belgrader P;Ryvkin P;Bent ZW;Wilson R;Ziraldo SB;Wheeler TD;McDermott GP;Zhu J;Gregory MT;Shuga J;Montesclaros L;Underwood JG;Masquelier DA;Nishimura SY;Schnall-Levin M;Wyatt PW;Hindson CM;Bharadwaj R;Wong A;Ness KD;Beppu LW;Deeg HJ;McFarland C;Loeb KR;Valente WJ;Ericson NG;Stevens EA;Radich JP;Mikkelsen TS;Hindson BJ;Bielas JH
通讯作者:
Bielas JH