Benchmarking single-cell RNA-sequencing protocols for cell atlas projects
Benchmarking single-cell RNA-sequencing protocols for cell atlas projects
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DOI：
10.1038/s41587-020-0469-4
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发表时间：
2020-04-06
影响因子：
46.9
通讯作者：
Heyn, Holger
中科院分区：
文献类型：
--
作者：
Mereu, Elisabetta;Lafzi, Atefeh;Heyn, Holger
一项多中心研究比较了13种常用的单细胞RNA测序方案。单细胞RNA测序（scRNA-seq）是表征样品中单个细胞转录组的领先技术。最新的协议可扩展到数千个细胞，并被用于编译组织，器官和生物体的细胞图谱。然而，这些方案在RNA捕获效率、偏倚、规模和成本方面存在很大差异，并且它们在不同应用中的相对优势尚不清楚。在本研究中，我们生成了基准数据集，以系统地评估协议全面描述细胞类型和状态的能力。我们进行了一项多中心研究，比较了13种常用的scRNA-seq和单核RNA-seq方案，这些方案应用于异质参考样本资源。比较分析显示，协议性能存在显著差异。这些方案在文库复杂性和它们检测细胞类型标志物的能力方面不同，影响它们的预测值和整合到参考细胞图谱中的适用性。这些结果为个人研究人员和联合项目（如人类细胞图谱）提供了指导。
A multicenter study compares 13 commonly used single-cell RNA-seq protocols.Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas.