ArticleGenome biology2025
SpatialLeiden: spatially aware Leiden clustering.
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 8 papers.
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.
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Who cites it
8 citing papers in PubMed.
- Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data.Nature methods · 2026Article
- A 3D spatial proteomic map of the human pancreatic islet microenvironment.Research square · 2026Article
- spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning.Bioinformatics (Oxford, England) · 2026Article
- Interpretable, flexible and spatially aware integration of multiple spatial transcriptomics datasets from diverse sources.Nature genetics · 2026Article
- Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection.Nature communications · 2026Article
- Deciphering immunosuppressive niches by spatial single-cell proteomics: spatial interaction networks and translational opportunities.Frontiers in immunology · 2026Review
- Functional genomics and tumor microenvironment analysis reveal prognostic biological subtypes in Mantle cell lymphoma.Nature communications · 2025Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clustering can identify the natural structure that is inherent to measured data. For single-cell omics, clustering finds cells with similar molecular phenotype after which cell types are annotated. Leiden clustering is one of the algorithms of choice in the single-cell community. In the field of spatial omics, Leiden is often categorized as a "non-spatial" clustering method. However, we show that by integrating spatial information at various steps Leiden clustering is rendered into a computationally highly performant, spatially aware clustering method that compares well with state-of-the art spatial clustering algorithms.
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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.