ArticleGenome biology2025
stDyer enables spatial domain clustering with dynamic graph embedding.
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 7 papers.
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Who cites it
7 citing papers in PubMed.
- spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning.Bioinformatics (Oxford, England) · 2026Article
- HarveST uses a heterogeneous graph learning framework to reveal spatial transcriptomics patterns.Communications biology · 2026Article
- stDyer-image improves clustering analysis of spatially resolved transcriptomics and proteomics with morphological images.Bioinformatics (Oxford, England) · 2026Article
- MaskGraphene: an advanced framework for interpretable joint representation for multi-slice, multi-condition spatial transcriptomics.Genome biology · 2025Article
- stTrace: detecting spatial-temporal domains from spatial transcriptome to trace developmental path.Briefings in bioinformatics · 2025Article
- spCLUE: a contrastive learning approach to unified spatial transcriptomics analysis across single-slice and multi-slice data.Genome biology · 2025Article
- stDyer enables spatial domain clustering with dynamic graph embedding.Genome biology · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Spatially resolved transcriptomics (SRT) data provide critical insights into gene expression patterns within tissue contexts, necessitating effective methods for identifying spatial domains. We introduce stDyer, an end-to-end deep learning framework for spatial domain clustering in SRT data. stDyer combines Gaussian Mixture Variational AutoEncoder with graph attention networks to learn embeddings and perform clustering. Its dynamic graphs adaptively link units based on Gaussian Mixture assignments, improving clustering and producing smoother domain boundaries. stDyer's mini-batch strategy and multi-GPU support facilitate scalability to large datasets. Benchmarking against state-of-the-art tools, stDyer demonstrates superior performance in spatial domain clustering, multi-slice analysis, and large-scale dataset handling.
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Registered trials
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