Chen Wanze, Gardeux Vincent, Meireles-Filho Antonio, Deplancke Bart
Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Curr Protoc Mouse Biol. 2017 Sep 8;7(3):145-175. doi: 10.1002/cpmo.30.
Complex biological systems are composed of multiple cell types whose transcriptional activity can vary due to differences in cell state, environmental stimulation, or intrinsic programs. Conventional bulk analysis methods capture the average transcriptional programs of the cell population, thus missing the unique cellular signature of each single cell. In recent years, the development of single-cell RNA-sequencing (scRNA-seq) technologies has provided a powerful approach to dissect the cellular heterogeneity of complex biological systems. However, such approaches require specialized equipment or are costly. In this article, we describe an improved Smart-seq2-based method to profile the transcriptome of hundreds of single cells simultaneously, without utilizing commercial kits or requiring any specialized single-cell capture/library preparation tools. Moreover, we introduce the Automated Single-cell Analysis Pipeline (ASAP), which allows researchers without strong computational expertise to explore scRNA-seq data using a wide range of commonly used algorithms and sophisticated visualization tools. © 2017 by John Wiley & Sons, Inc.
复杂的生物系统由多种细胞类型组成，其转录活性会因细胞状态、环境刺激或内在程序的差异而有所不同。传统的批量分析方法捕获的是细胞群体的平均转录程序，因此会遗漏每个单细胞独特的细胞特征。近年来，单细胞RNA测序（scRNA-seq）技术的发展为剖析复杂生物系统的细胞异质性提供了一种强大的方法。然而，此类方法需要专门的设备或成本高昂。在本文中，我们描述了一种基于Smart-seq2改进的方法，可同时对数百个单细胞的转录组进行分析，无需使用商业试剂盒，也不需要任何专门的单细胞捕获/文库制备工具。此外，我们还介绍了自动单细胞分析管道（ASAP），它使没有强大计算专业知识的研究人员能够使用广泛的常用算法和复杂的可视化工具来探索scRNA-seq数据。© 2017 John Wiley & Sons, Inc.
