Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically

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.

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Publication Details

Journal
Cells
Published
2025-06-30
DOI
https://doi.org/10.3390/cells14131000
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically

Ricardo Melo Ferreira, Michael T. Eadon, Yanchun Liang, Juexin Wang et al.
Cells
Single-cell and spatial transcriptomics
article

Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically

Ricardo Melo Ferreira, Michael T. Eadon, Yanchun Liang, Juexin Wang, Dong Xu, Yan Wang, Yu Lin, Mauminah Raina
article en

Abstract

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.

CellsVol. 14(13)
Jilin University (CN), Zhuhai Institute of Advanced Technology (CN), Indiana University Indianapolis (US), Indiana University – Purdue University Indianapolis (US), University of Missouri (US)
National Natural Science Foundation of China
Decent work and economic growth
Openalex Percentile: Top 86%
Single-cell and spatial transcriptomics
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