Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA; email:
Biomedical Sciences Graduate Program, University of California, San Francisco, California, USA.
Annu Rev Biomed Data Sci. 2023 Aug 10;6:47-71. doi: 10.1146/annurev-biodatasci-020422-050255. Epub 2023 Apr 11.
Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.
单细胞蛋白质组学技术的进步产生了包含数百万个细胞的高维数据集，这些数据集能够回答关于生物学和疾病的关键问题。这些技术的出现促使人们开发了计算工具来处理和可视化复杂的数据。在这篇综述中，我们概述了单细胞和空间蛋白质组学分析管道的步骤。除了描述可用的方法外，我们还强调了基准测试研究，这些研究确定了当前可用的计算工具包的优缺点。随着这些技术的不断进步，应该开发强大的分析工具，以充分利用这些数据提供的潜在生物学见解。
