Abstract：
The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.
摘要：
单细胞RNA测序（scRNA-seq）在生物医学研究中的应用促进了我们对疾病发病机理的理解，并为新的诊断和治疗策略提供了有价值的见解。随着高通量scRNA-seq容量的扩大，包括临床样本,对于进入这一领域的研究人员来说，对这些大量数据的分析已经成为一个令人生畏的前景。这里,我们回顾了典型的scRNA-seq数据分析的工作流程，涵盖原始数据处理和质量控制，适用于几乎所有scRNA-seq数据集的基本数据分析，和先进的数据分析，应针对特定的科学问题。在总结每个分析步骤的当前方法的同时，我们还提供了一个软件和包装脚本的在线存储库来支持实施。指出了一些特定分析任务和方法的建议和注意事项。我们希望这个资源将有助于研究人员参与scRNA-seq，特别是对于新兴的临床应用。
