ArticleNature communications2025
Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A multiperspective evaluation framework of spatial transcriptomics clustering methods.NAR genomics and bioinformatics · 2026Article
- STWave: Fine-Scale Spatial Structure Discovery in Microscopic-Resolution Spatial Transcriptomics via Patchwise Wavelet Graphs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning.Bioinformatics (Oxford, England) · 2026Article
- Empowering multifaceted analysis of spatial transcriptomics data with RGAST.Briefings in bioinformatics · 2026Article
- Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST.Nature communications · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
We propose HERGAST, a system for spatial structure identification and signal amplification in ultra-large-scale and ultra-high-resolution spatial transcriptomics data. To handle ultra-large spatial transcriptomics (ST) data, we consider the divide and conquer strategy and devise a Divide-Iterate-Conquer framework especially for spatial transcriptomics data analysis, which can also be adopted by other computational methods for extending to ultra-large-scale ST data analysis. To tackle the potential over-smoothing problem arising from data splitting, we construct a heterogeneous graph network to incorporate both local and global spatial relationships. In simulations, HERGAST consistently outperforms other methods across all settings with more than a 10% increase in average adjusted rand index (ARI). In real-world datasets, HERGAST's high-precision spatial clustering identifies SPP1+ macrophages intermingled within colorectal tumors, while the enhanced gene expression signals reveal unique spatial expression patterns of key genes in breast cancer.
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Registered trials
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