ArticleNature methods2025
Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
131 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Enhancing RNA Capture Efficiency in Spatial Transcriptomics: A Review of Innovative Technologies and Strategies.International journal of molecular sciences · 2025Pooled it
- High-resolution spatial transcriptomics of irradiated submandibular glands treated with fortified fibrin hydrogels.iScience · 2026Article
- Serval: A modular framework for decoding imaging based spatial transcriptomics data.Bioinformatics (Oxford, England) · 2026Article
- Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.The Plant cell · 2026Review
- Unraveling the tapestry: Lessons from multi-omics and spatial biology in hepatocellular cancer.Hepatology (Baltimore, Md.) · 2026Review
- Insights Into Spatial Transcriptomics: Exploring Recent Technical Developments and Their Diverse Applications.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Review
- Spatial transcriptomic analysis of neurons at the glioma infiltration front: A case study.Brain pathology (Zurich, Switzerland) · 2026Article
- Cell atlas of the developing human meninges reveals a dura-like nature of meningiomas.Nature cell biology · 2026Article
- HIGH-DIMENSIONAL MULTI-OMIC MAPPING OF POST-MORTEM HUMAN BRAIN USING ITERATIVE INDIRECT IMMUNOFLUORESCENCE IMAGING ON XENIUM-PROCESSED TISSUES.bioRxiv : the preprint server for biology · 2026Article
- Article
- Spatial proteogenomic profiling uncovers sensitization strategies for antibody-drug conjugate in HER2-positive breast cancer.Cell reports. Medicine · 2026Article
- RNA-aware tissue preservation workflows for high-quality spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Quantitative dissection of the metastatic cascade at single colony resolution.Research square · 2026Article
- Review
- Advances in single-cell and spatial multi-omics for plant development and stress responses.Plant diversity · 2026Review
- Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.Nature methods · 2026Article
- KSTITCH links cellular morphology and gene expression in spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- CoxFormer enables spatial omics inference with multimodal generative modeling.Nature communications · 2026Article
- Spatial ecotype in tumor immune exclusion: from spatial architecture to therapeutic strategies.Molecular cancer · 2026Review
- Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.Nature communications · 2026Article
71 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.