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bioRxiv · 10.1101/2025.07.21.665821

OmicsNavigator: an LLM-driven multi-agent system for autonomous zero-shot biological analysis in spatial omics

LI, Y.·Vakharia, N.·Mayer, A. T.·Luo, R.·Trevino, A. E.·Wu, Z.
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Abstract

Translating high-dimensional, spatially resolved molecular datasets into testable biological findings remains a major research bottleneck. Here, we present Omic-sNavigator, an autonomous large language model-powered system for end-to-end data exploration and hypothesis validation on spatial omics data. OmicsNaviga-tor reasons directly over the multi-modal inputs of spatial omics data, including visual and molecular signatures, to perform knowledge-guided annotation of spatial structures. We show that by transforming high-dimensional data into textual interpretations, OmicsNavigator enables zero-shot semantic retrieval of tissue biomarkers and the reconstruction of patient-level disease profiles from raw omics observations. Furthermore, OmicsNavigator features an objective hypothesis validation engine governed by pre-registered, human-audited blueprints. By validating the system across datasets spanning diverse pathological conditions including diabetic kidney disease, kidney transplant rejection, and COVID-19 pulmonary pathology, we demonstrate that OmicsNavigator generates evidence-based, human-readable insights from spatial omics data, with potential to accelerate spatial biology discoveries.

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LI, Y., Vakharia, N., Mayer, A. T., Luo, R., Trevino, A. E., Wu, Z.. 2025-07-25. OmicsNavigator: an LLM-driven multi-agent system for autonomous zero-shot biological analysis in spatial omics. https://doi.org/10.1101/2025.07.21.665821

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