STAPLE: automating spatial transcriptomics analysis and AI interpretation

Lvovs, D.; Quinn, J.; Forjaz, A.; Santana-Cruz, I.; Stapleton, O.; Vavikolanu, K.; Wetzel, M.; Data Science Hub TeamLab,; Demystifying Pancreatic Cancer Therapies TeamLab,; Pagan, V. B.; Herb, B. R.; Favorov, A.; Kagohara, L. T.; Kiemen, A. L.; Maitra, A.; Sidiropoulos, D. N.; Tansey, W.; Wood, L.; Deshpande, A.; Noble, M.; Fertig, E. J.

doi:10.64898/2026.03.30.715127

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bioRxiv · 10.64898/2026.03.30.715127

STAPLE: automating spatial transcriptomics analysis and AI interpretation

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Abstract

Spatial transcriptomics workflows often span separate tools for cell typing, neighborhoods, and cell-cell communication, yielding fragmented outputs that hinder scalability, interpretation, and reproducibility. STAPLE systematizes analyses across distinct methods into a modular framework, unifying data structures and cross-tool interoperability. End-to-end analyses are performed unassisted with a single invocation, fostering rigorous, reproducible spatial transcriptomics analysis. Its novel, AI-enabled reporting layer synthesizes quantitative results into summaries of biological findings, facilitating analysis interpretation.

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Lvovs, D., Quinn, J., Forjaz, A., Santana-Cruz, I., Stapleton, O., Vavikolanu, K., Wetzel, M., Data Science Hub TeamLab,, Demystifying Pancreatic Cancer Therapies TeamLab,, Pagan, V. B., Herb, B. R., Favorov, A., Kagohara, L. T., Kiemen, A. L., Maitra, A., Sidiropoulos, D. N., Tansey, W., Wood, L., Deshpande, A., Noble, M., Fertig, E. J.. 2026-04-01. STAPLE: automating spatial transcriptomics analysis and AI interpretation. https://doi.org/10.64898/2026.03.30.715127

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