ArticleGenome biology2025
SpaNorm: spatially-aware normalization for spatial transcriptomics data.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- Amplification bias in sequencing-based spatial transcriptomics: sources, mechanisms, impacts, and mitigation strategies.Briefings in bioinformatics · 2026Review
- Tumor microenvironment-specific nanomedicine: from biology-driven to multi-omics-guided precision engineering.Journal of hematology & oncology · 2026Review
- Logistic regression for estimating functional effects with spatial transcriptomics.Nucleic acids research · 2026Article
- From glycolytic signatures to patients: A translational roadmap for reproducible, equitable deployment of multi-omics and AI in colorectal cancer.Medical oncology (Northwood, London, England) · 2026Article
- Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.Cancer cell · 2026Review
- Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?Briefings in bioinformatics · 2026Article
- From Raw Data to Biological Insights: A Practical Guide for Spatial Transcriptomics Analysis in R and Python.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Spatial Transcriptomics of Adipose Tissue: Technologies, Applications, and Challenges.Journal of obesity & metabolic syndrome · 2025Review
- Mapping disease critical spatially variable gene programs by integrating spatial transcriptomics with human genetics.bioRxiv : the preprint server for biology · 2025Article
- Harnessing the potential of spatial statistics for spatial omics data with pasta.Nucleic acids research · 2025Article
- Integrating spatial omics with routine haematoxylin and eosin in formalin-fixed paraffin-embedded: a step-by-step clinical workflow.F1000Research · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Normalization of spatial transcriptomics data is challenging due to spatial association between region-specific library size and biology. We develop SpaNorm, the first spatially-aware normalization method that concurrently models library size effects and the underlying biology, segregates these effects, and thereby removes library size effects without removing biological information. Using 27 tissue samples from 6 datasets spanning 4 technological platforms, SpaNorm outperforms commonly used single-cell normalization approaches while retaining spatial domain information and detecting spatially variable genes. SpaNorm is versatile and works equally well for multicellular and subcellular spatial transcriptomics data with relatively robust performance under different segmentation methods.
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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.