Lin Yu, Wang Yan, Wang Juexin, Raina Mauminah, Ferreira Ricardo Melo, Eadon Michael T, Liang Yanchun, Xu Dong
School of Artificial Intelligence, Jilin University, Changchun 130012, China.
Department of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.
Cells. 2025 Jun 30;14(13):1000. doi: 10.3390/cells14131000.
10X Xenium is an in situ spatial transcriptomics platform that enables single-cell and subcellular-level gene expression analysis. In Xenium data analysis, defining matched keypoints to align H&E and spatial transcriptomic images is critical for cross-referencing sequencing and histology. Currently, it is labor-intensive for domain experts to manually place keypoints to perform image registration in the Xenium Explorer software. We present Xenium-Align, a keypoint identification method that automatically generates keypoint files for image registration in Xenium Explorer. We validated our proposed method on 14 human kidney samples and one human skin Xenium sample representing healthy and diseased states, with expert manually marked results. These results show that Xenium-Align could generate accurate keypoints for automatically implementing image alignment in the Xenium Explorer software for spatial transcriptomics studies. Our future research aims to optimize the method's runtime efficiency and usability for image alignment applications.
10X Xenium是一个原位空间转录组学平台，可实现单细胞和亚细胞水平的基因表达分析。在Xenium数据分析中，定义匹配的关键点以对齐苏木精和伊红（H&E）染色图像与空间转录组图像对于交叉引用测序和组织学至关重要。目前，领域专家在Xenium Explorer软件中手动放置关键点以执行图像配准的工作强度很大。我们提出了Xenium-Align，这是一种关键点识别方法，可自动生成用于在Xenium Explorer中进行图像配准的关键点文件。我们在14个人类肾脏样本和1个人类皮肤Xenium样本（代表健康和患病状态）上验证了我们提出的方法，并与专家手动标记的结果进行了对比。这些结果表明，Xenium-Align可以生成准确的关键点，以便在用于空间转录组学研究的Xenium Explorer软件中自动实现图像对齐。我们未来的研究旨在优化该方法在图像对齐应用中的运行时效率和可用性。
