Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows

The Xenium In Situ platform is a new spatial transcriptomics product commercialized by 10x Genomics, capable of mapping hundreds of genes in situ at subcellular resolution. Given the multitude of commercially available spatial transcriptomics technologies, recommendations in choice of platform and analysis guidelines are increasingly important. Herein, we explore 25 Xenium datasets generated from multiple tissues and species, comparing scalability, resolution, data quality, capacities and limitations with eight other spatially resolved transcriptomics technologies and commercial platforms. In addition, we benchmark the performance of multiple open-source computational tools, when applied to Xenium datasets, in tasks including preprocessing, cell segmentation, selection of spatially variable features and domain identification. This study serves as an independent analysis of the performance of Xenium, and provides best practices and recommendations for analysis of such datasets.

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Publication Details

Journal
Nature Methods
Published
2025-03-13
DOI
https://doi.org/10.1038/s41592-025-02617-2
Citations
68
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
54.81

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article

Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows

Mats F. Nilsson, Christophe Avenel, Sergio Marco Salas, Carolina Wählby et al.
68 citations
Nature Methods
Single-cell and spatial transcriptomics
54.81
article

Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows

Mats F. Nilsson, Christophe Avenel, Sergio Marco Salas, Carolina Wählby, Axel Andersson, Naveed Ishaque, Malte D. Luecken, Paulo Czarnewski, Habib Rehman, Marco Grillo, Nima Rafati, Taobo Hu, Louis B. Kuemmerle, Fabian Joachim Theis, Saga Helgadóttir, Katarína Tiklová, Maria Chatzinikolaou, Sebastian Tismeyer, Christoffer Mattsson-Langseth
article en
68 citations

Abstract

The Xenium In Situ platform is a new spatial transcriptomics product commercialized by 10x Genomics, capable of mapping hundreds of genes in situ at subcellular resolution. Given the multitude of commercially available spatial transcriptomics technologies, recommendations in choice of platform and analysis guidelines are increasingly important. Herein, we explore 25 Xenium datasets generated from multiple tissues and species, comparing scalability, resolution, data quality, capacities and limitations with eight other spatially resolved transcriptomics technologies and commercial platforms. In addition, we benchmark the performance of multiple open-source computational tools, when applied to Xenium datasets, in tasks including preprocessing, cell segmentation, selection of spatially variable features and domain identification. This study serves as an independent analysis of the performance of Xenium, and provides best practices and recommendations for analysis of such datasets.

Nature MethodsVol. 22(4)
Uppsala University (SE), University of Illinois Urbana-Champaign (US), Stockholm University (SE), Science for Life Laboratory (SE), Helmholtz Zentrum München (DE), German Center for Lung Research (DE), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), KTH Royal Institute of Technology (SE)
Chan Zuckerberg Initiative, Bundesministerium für Bildung und Forschung, Cancerfonden, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
54.81
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