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Investigating Spatial Dynamics in Spatial Omics Data with StarTrail
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DOI：10.1080/01621459.2026.2654225.png)
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Abstract
En 中文
Spatial omics technologies revolutionize our view of biological processes within tissues. However, existing methods fail to capture localized, sharp changes characteristic of critical events (e.g., tumor development). Here, we present StarTrail, a novel gradient based method that powerfully defines rapidly changing regions and detects “cliff genes”, genes exhibiting drastic expression changes at highly localized or disjoint boundaries. StarTrail, the first to leverage spatial gradients for spatial omics data, also quantifies directional dynamics. Across multiple datasets, StarTrail accurately delineates boundaries (e.g., brain layers, tumor-immune boundaries), and detects cliff genes that may regulate molecular crosstalk at these biologically relevant boundaries but are missed by existing methods. StarTrail, filling important gaps in current literature, enables deeper insights into tissue spatial architecture. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
Keywords:
Boundary detection
Cliff gene
Gaussian Process
gradients
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J
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3
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5.1K
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