Spatially Anchored Regulatory State Inference in Melanoma

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Jagan Mohan Reddy Dwarampudi, Veena Kochat, Suresh Satpati, Md Ishtyaq Mahmud, Humaira Anzum, Khalida Wani, Alexander Lazar, Ajay Kumar Saw, Jared Malke, Hien V. Nguyen, Kunal Rai, Tania Banerjee

Published: 08 Apr 2026, Last Modified: 06 May 2026CrossrefEveryoneRevisionsCC BY-SA 4.0
Abstract: Spatial transcriptomics (ST) captures gene expression within tissue architecture but lacks direct regulatory information, while single-cell multiome assays profile transcriptional and chromatin states without spatial context. We present a framework for spatially anchored regulatory inference that integrates Visium ST with single-cell multiome data to infer spatially resolved regulatory programs. Building upon GraphST, we introduce spatially regularized cell-to-spot mapping and propagate chromatin accessibility and transcription factor motif activity into tissue space. Regulatory analysis is performed at the spatial domain level via joint differential expression and accessibility testing, along with quantitative concordance assessment. Applied to melanoma tissue sections, the framework reveals spatially localized regulatory programs and shows that assignment strategy substantially affects downstream regulatory stability. This modular approach enables interpretable gene-, peak-, and transcription factor–level outputs for multimodal spatial analysis.