Spatial transcriptomics: integrating platforms and computational approaches for clinical insights

Spatial transcriptomics (ST) is a significant advancement in life science research, enabling transcriptome analysis to transition from traditional bulk and single-cell levels to spatial location levels, thereby expanding the boundaries of biological research and pathological diagnosis. This technological breakthrough has provided unprecedented insights into complex biological processes, disease mechanisms, and clinical diagnosis. Despite the impressive advances in the field in recent years, it still faces several challenges, including technical complexity, difficulties in data analysis, and the lack of standardization. This review provides a comprehensive comparison of the technical principles and data analysis processes of ST, while also summarizing its latest applications and the current state of standardization. It aims to provide researchers with a clear framework for understanding the progresses, challenges, and future directions, thereby promoting the further development and clinical transition of ST technologies.