Systematic comparison of single-cell and single-nucleus RNA-sequencing methods
Systematic comparison of single-cell and single-nucleus RNA-sequencing methods
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DOI：
10.1038/s41587-020-0465-8
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发表时间：
2020-04-06
影响因子：
46.9
通讯作者：
Levin, Joshua Z.
中科院分区：
文献类型：
--
作者：
Ding, Jiarui;Adiconis, Xian;Levin, Joshua Z.
单细胞RNA测序的七种方法以细胞系、原代细胞和小鼠皮质为基准。近年来，单细胞RNA测序方法的规模和能力迅速扩大，使重大发现和大规模细胞图谱工作成为可能。然而，这些方法尚未进行系统和全面的基准测试。在这里，我们直接比较了七种用于单细胞和/或单核分析的方法-根据它们的使用情况和我们的专业知识和资源选择代表性方法来制备文库-包括两种低通量和五种高通量方法。我们在三种类型的样本上测试了这些方法：细胞系、外周血单核细胞和脑组织，在一个中心的六个独立实验中生成了36个文库。为了直接比较这些方法并避免现有管道引入的处理差异，我们开发了scumi，这是一种灵活的计算管道，可用于任何单细胞RNA测序方法。我们评估了这些方法的基本性能，如读段的结构和比对、多重峰的灵敏度和范围，以及它们恢复样品中已知生物信息的能力。
Seven methods for single-cell RNA sequencing are benchmarked on cell lines, primary cells and mouse cortex.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.