Investigating Spatial Dynamics in Spatial Omics Data with StarTrail

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Authors: Jiawen Chen, Caiwei Xiong, Quan Sun, Yutong Song, Geoffery W. Wang, Gaorav P. Gupta, Aritra Halder, Didong Li, Didong Li
Cited by: 4
References: 71

Abstract

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.

Fields of Study & Subjects

Atmospheric and Environmental Gas Dynamics Vehicle emissions and performance

Publication details

Journal / source
Journal of the American Statistical Association
Publisher
Informa UK Limited
Pages
1–12
Publication date
7 July 2026
Language
EN