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bioRxiv · 10.64898/2025.12.30.697018

Multi-task spatial omics analytics for high-precision modeling of tissue architecture with STAX

Guo, Z.-H.·Huang, D.-S.·Zhang, S.
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Abstract

The rapid advancement of spatial omics technology has revolutionized biomedical research, unveiling unprecedented insights into the molecular and cellular architecture of biological systems. Despite this progress, a critical limitation arises from the widespread use of disparate analytical tools within a single workflow, leading to inconsistencies caused by heterogeneous preprocessing pipelines and extensive method-specific hyperparameter tuning. To this end, we aim to unify diverse analytical tasks within a multi-task learning platform, STAX, for diverse spatial omics types. STAX excels across numerous critical applications, including spatial domain identification, spatial slice integration, cohort-level spatial analysis, spatial spot completion, cell-gene co-embedding, expression profile denoising, and 3D spatial multi-slice simulation. Extensive evaluations demonstrate that STAX consistently delivers superior performance, robustness, and biologically meaningful interpretations, establishing it as an indispensable tool for spatial omics research. In short, STAX effectively addresses multiple analytical challenges in spatial omics, empowering researchers with a unified platform to accelerate biomedical discoveries and deepen understanding of complex biological systems.

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Guo, Z.-H., Huang, D.-S., Zhang, S.. 2025-12-30. Multi-task spatial omics analytics for high-precision modeling of tissue architecture with STAX. https://doi.org/10.64898/2025.12.30.697018

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