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<p>Spatial transcriptomics enables gene expression mapping within tissues but is often limited by imaging constraints. We present an imaging-free approach that reconstructs spatial barcode locations using molecular diffusion and dimensionality reduction. Validated against ground truth imaging, our method achieves high fidelity and scales to centimeter-sized tissues. This approach enhances spatial transcriptomics’ accessibility and throughput, enabling large-scale studies without specialized imaging equipment.</p>

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Scalable spatial transcriptomics through computational array reconstruction

  • 期刊论文

  • 发表日期：

    2025年4月3日

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  • Chenlei Hu,
  • Mehdi Borji,
  • Giovanni J. Marrero,
  • Vipin Kumar,
  • Jackson A. Weir,
  • Sachin V. Kammula,
  • Evan Z. Macosko,
  • Fei Chen

摘要

Spatial transcriptomics enables gene expression mapping within tissues but is often limited by imaging constraints. We present an imaging-free approach that reconstructs spatial barcode locations using molecular diffusion and dimensionality reduction. Validated against ground truth imaging, our method achieves high fidelity and scales to centimeter-sized tissues. This approach enhances spatial transcriptomics’ accessibility and throughput, enabling large-scale studies without specialized imaging equipment.