Brief Funct Genomics. 2022 Jul 27;21(4):280-295. doi: 10.1093/bfgp/elac011.
With the rapid advancement in sequencing technologies, the concept of omics has revolutionized our understanding of cellular behaviors. Conventional omics investigation approaches measure the averaged behaviors of multiple cells, which may easily hide signals represented by a small-cell cohort, urging for the development of techniques with enhanced resolution. Single-cell RNA sequencing, investigating cell transcriptomics at the resolution of a single cell, has been rapidly expanded to investigate other omics such as genomics, proteomics and metabolomics since its invention. The requirement for comprehensive understanding of complex cellular behavior has led to the integration of multi-omics and single-cell sequencing data with other layers of information such as spatial data and the CRISPR screening technique towards gained knowledge or innovative functionalities. The development of single-cell sequencing in both dimensions has rendered it a unique field that offers us a versatile toolbox to delineate complex diseases, including cancers.
随着测序技术的飞速发展，组学概念彻底改变了我们对细胞行为的理解。传统的组学研究方法测量的是多个细胞的平均行为，这可能很容易掩盖由一小部分细胞代表的信号，因此需要开发具有更高分辨率的技术。单细胞 RNA 测序自发明以来，已经迅速扩展到研究其他组学，如基因组学、蛋白质组学和代谢组学，以在单细胞分辨率上研究细胞转录组学。为了全面了解复杂的细胞行为，人们需要将多组学和单细胞测序数据与其他层次的信息（如空间数据和 CRISPR 筛选技术）进行整合，以获得新知识或创新功能。单细胞测序在这两个维度上的发展，使其成为一个独特的领域，为我们提供了一个多功能的工具箱，用于描绘复杂疾病，包括癌症。
