State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, China.
School of Medicine, Southeast University, Nanjing, China.
IET Nanobiotechnol. 2023 May;17(3):246-256. doi: 10.1049/nbt2.12115. Epub 2023 Feb 2.
With the development of single-cell RNA sequencing technology (scRNA-seq), we have the ability to study biological questions at the level of the individual cell transcriptome. Nowadays, many analysis tools, specifically suitable for single-cell RNA sequencing data, have been developed. In this review, the currently commonly used scRNA-seq protocols are discussed. The upstream processing flow pipeline of scRNA-seq data, including goals and popular tools for reads mapping and expression quantification, quality control, normalization, imputation, and batch effect removal is also introduced. Finally, methods to evaluate these tools in both cellular and genetic dimensions, clustering and differential expression analysis are presented.
随着单细胞 RNA 测序技术（scRNA-seq）的发展，我们有能力在单个细胞转录组水平上研究生物学问题。如今，已经开发出许多专门适用于单细胞 RNA 测序数据的分析工具。在这篇综述中，讨论了目前常用的 scRNA-seq 方案。还介绍了 scRNA-seq 数据的上游处理流程管道，包括读取映射和表达定量、质量控制、标准化、插补和批次效应去除的目标和流行工具。最后，还介绍了在细胞和遗传维度上评估这些工具的方法，包括聚类和差异表达分析。
