ArticleNature genetics2024
BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis.
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 1 of them a synthesis that pooled it.
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Who cites it
174 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cross-expression meta-analysis of mouse brain slices reveals coordinated gene expression across spatially adjacent cells.Genome biology · 2025Pooled it
- Cadmium Exposure and Osteoporosis: A Spatially Contextualized Adverse Outcome Pathway Integrating Epidemiology, Toxicogenomics and Transcriptomics.Biological trace element research · 2026Article
- Multiplatform single-cell and spatial transcriptomics reveal sex-specific malignant states and architecture in male breast cancer.Science advances · 2026Article
- Article
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- Reduction of forebrain interneurons alters cellular organization and cortical neurogenesis in a mouse model of X-linked intellectual disability.bioRxiv : the preprint server for biology · 2026Article
- Kintsugi decides, gene by gene, where spatial transcriptomics borrows information.bioRxiv : the preprint server for biology · 2026Article
- Microenvironment-aware transcriptome reconstruction in spatial transcriptomics.Nature communications · 2026Article
- Decoding cell-cell communication in spatial transcriptomics: mechanistic insights, modeling constraints, and analytical caveats.Briefings in bioinformatics · 2026Review
- Progenitor T cells drive chronic pulmonary type 2 inflammation.Nature immunology · 2026Article
- Human and mouse adrenal glands are characterized by species-specific steroidogenic states and tissue turnover.Nature genetics · 2026Article
- HESTIA: scalable multimodal integration of histology and high-resolution spatial Transcriptomics for robust spatial domain identification.Briefings in bioinformatics · 2026Article
- DPAS-Graph: adaptive spatial-feature relation learning for spatial RNA-to-protein prediction and virtual protein profiling.Briefings in bioinformatics · 2026Article
- Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.Nature methods · 2026Article
- SemanticST: A Scalable Multi-Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi-Sample Integration in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Benchmarking cell type annotation in spatial transcriptomics: resolving cellular hierarchies, biological fidelity, and dynamic cell states.Research square · 2026Article
- Evaluating exon skipping in the central nervous system in Duchenne muscular dystrophy using spatial transcriptomics.iScience · 2026Article
- Fzd7 Restrains Pink1-Dependent Mitophagy in Suture Stem Cells to Maintain Cranial Suture Patency.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- PD-1 regulates CD4Nature communications · 2026Article
- Myasthenia thymus reprograms class-switched B cells into BAFF-dependent survivors.Science advances · 2026Article
114 more citing papers are in PubMed but not listed here.
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Authors and funding
13 authors.
Funding
Abstract
Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.
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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.