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

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

引用：Marco Salas S, Kuemmerle LB, Mattsson-Langseth C, Tismeyer S, Avenel C, Hu T, Rehman H, Grillo M, Czarnewski P, Helgadottir S, Tiklova K, Andersson A, Rafati N, Chatzinikolaou M, Theis FJ, Luecken MD, Wählby C, Ishaque N, Nilsson M. (2025). Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows. Nature methods. PMID 40082609 · PMC11978515 · DOI 10.1038/s41592-025-02617-2

证据类型：METHODS

主题：rna-seq、spatial-omics

被引次数（采集时）：86

原始记录：[Europe PMC](https://europepmc.org/article/MED/40082609)

来源许可：[CC-BY](https://creativecommons.org/licenses/by/)

作者摘要（按来源许可复用）

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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