ArticleGenome biology2025
ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysis.
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 4 papers.
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Who cites it
4 citing papers in PubMed.
- StPedf: Cell trajectory inference of spatial transcriptomics via spatial proximity embedding and spatial density-adaptive fusion.PLoS computational biology · 2026Article
- Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro.bioRxiv : the preprint server for biology · 2026Article
- HRCHY-CytoCommunity identifies hierarchical tissue organization in cell-type spatial maps.Nature communications · 2026Article
- ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysis.Genome biology · 2025Article
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Abstract
Recent technological advances enable mapping of tissue spatial organization at single-cell resolution, but methods for analyzing spatially continuous microenvironments are still lacking. We introduce ONTraC, a graph neural network-based framework for constructing spatial trajectories at niche-level. Through benchmarking analyses using multiple simulated and real datasets, we show that ONTraC outperforms existing methods. ONTraC captures both normal anatomical structures and disease-associated tissue microenvironment changes. In addition, it identifies tissue microenvironment-dependent shifts in gene expression, regulatory network, and cell-cell interaction patterns. Taken together, ONTraC provides a useful framework for characterizing the structural and functional organization of tissue microenvironments.
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