新研究系统性比较单细胞和单核RNA测序方法

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本期文章:《自然—生物技术》:Online/在线发表

美国麻省理工学院和哈佛大学博德研究所Joshua Z. Levin团队对单细胞和单核RNA测序方法进行了系统比较。2020年4月6日,《自然—生物技术》在线发表了这一成果。

近年来,单细胞RNA测序方法的规模和能力迅速扩展,从而实现了重大发现和大规模的细胞作图工作。但是,这些方法尚未得到系统和全面的基准测试。

研究人员直接比较了用于单细胞和/或单细胞核测序的七种方法,包括两种低通量方法和五种高通量方法。研究人员在三种类型的样品上测试了这些方法:细胞系、外周血单个核细胞和脑组织,并在6个独立实验中获得了36个文库。

为了直接比较方法并避免现有流程引入的处理差异,研究人员开发了scumi,这是一种灵活的计算流程,可与任何单细胞RNA测序方法一起使用。

研究人员评估了这些方法的基本性能,例如读数的结构和比对、敏感性和多重峰的范围,以及它们在样品中重复已知生物学信息的能力。

附:英文原文

Title: Systematic comparison of single-cell and single-nucleus RNA-sequencing methods

Author: Jiarui Ding, Xian Adiconis, Sean K. Simmons, Monika S. Kowalczyk, Cynthia C. Hession, Nemanja D. Marjanovic, Travis K. Hughes, Marc H. Wadsworth, Tyler Burks, Lan T. Nguyen, John Y. H. Kwon, Boaz Barak, William Ge, Amanda J. Kedaigle, Shaina Carroll, Shuqiang Li, Nir Hacohen, Orit Rozenblatt-Rosen, Alex K. Shalek, Alexandra-Chlo Villani, Aviv Regev, Joshua Z. Levin

Issue&Volume: 2020-04-06

Abstract: The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling—selecting representative methods based on their usage and our expertise and resources to prepare libraries—including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

DOI: 10.1038/s41587-020-0465-8

Source: https://www.nature.com/articles/s41587-020-0465-8

期刊信息

Nature Biotechnology:《自然—生物技术》,创刊于1996年。隶属于施普林格·自然出版集团,最新IF:31.864
官方网址:https://www.nature.com/nbt/
投稿链接:https://mts-nbt.nature.com/cgi-bin/main.plex

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