利用基于膜的边界定义和增强的单细胞分辨率改进空间转录组学（小方法5/2025）

IF 10.7 2区材料科学 Q1 CHEMISTRY, PHYSICAL

Small Methods Pub Date : 2025-05-24 DOI:10.1002/smtd.202570034

Li Song, Liqun Wang, Zitian He, Xiao Cui, Cheng Peng, Jie Xu, Zhouying Yong, Yanmei Liu, Ji-Feng Fei

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引用次数: 0

摘要

单细胞分辨率在文章编号2401056中，刘燕梅，费吉峰等介绍了一种细胞膜遗传标记模型，用于精确定义基于测序的空间转录组学中的细胞边界。这项工作表明，与细胞核或基于算法的方法相比，基于细胞膜的细胞分割更准确地代表了实际组织和器官中的真实单细胞，特别是在不规则和多核细胞的情况下，从而提高了单细胞分辨率并增强了空间转录组学的分析能力。

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Improving Spatial Transcriptomics with Membrane-Based Boundary Definition and Enhanced Single-Cell Resolution (Small Methods 5/2025)

Single-Cell Resolution

In article number 2401056, Yanmei Liu, Ji-Feng Fei, and co-workers introduce a cell membrane genetic-labeling model to precisely define cell boundaries in sequencing-based spatial transcriptomics. This work demonstrates that cell segmentation based on cell membranes more accurately represents the true single cells in actual tissues and organs compared to nucleus or algorithmic-based methods, particularly in the case of irregular and multinucleated cells, thereby improving single-cell resolution and enhancing the analytical power of spatial transcriptomics.

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来源期刊

Small Methods Materials Science-General Materials Science

CiteScore

17.40

自引率

1.60%

发文量

347

期刊介绍： Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.