Literature DB >> 28092691

Effective detection of variation in single-cell transcriptomes using MATQ-seq.

Kuanwei Sheng1,2, Wenjian Cao1, Yichi Niu1, Qing Deng1, Chenghang Zong1,2,3,4.   

Abstract

The quantification of transcriptional variation in single cells, particularly within the same cell population, is currently limited by the low sensitivity and high technical noise of single-cell RNA-seq assays. We report multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq), a highly sensitive and quantitative method for single-cell sequencing of total RNA. By systematically determining technical noise, we show that MATQ-seq captures genuine biological variation between whole transcriptomes of single cells.

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Year:  2017        PMID: 28092691     DOI: 10.1038/nmeth.4145

Source DB:  PubMed          Journal:  Nat Methods        ISSN: 1548-7091            Impact factor:   28.547


  58 in total

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Authors:  Neus Bota-Rabassedas; Priyam Banerjee; Yichi Niu; Wenjian Cao; Jiayi Luo; Yuanxin Xi; Xiaochao Tan; Kuanwei Sheng; Young-Ho Ahn; Sieun Lee; Edwin Roger Parra; Jaime Rodriguez-Canales; Jacob Albritton; Michael Weiger; Xin Liu; Hou-Fu Guo; Jiang Yu; B Leticia Rodriguez; Joshua J A Firestone; Barbara Mino; Chad J Creighton; Luisa M Solis; Pamela Villalobos; Maria Gabriela Raso; Daniel W Sazer; Don L Gibbons; William K Russell; Gregory D Longmore; Ignacio I Wistuba; Jing Wang; Harold A Chapman; Jordan S Miller; Chenghang Zong; Jonathan M Kurie
Journal:  Cell Rep       Date:  2021-04-20       Impact factor: 9.423

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