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bioRxiv · 10.1101/2025.10.23.683862

Histology-informed spatial domain identification through multi-view graph convolutional networks

Zhang, H.·Chang, J.·Sun, Y.·Hu, P.·Liu, J.·Luo, J.·Yang, H.·Ren, Y.·Zhang, X.·Chen, Z.·Wong, K. W.·Shao, H.
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Abstract

Identifying spatial domains is crucial in spatial transcriptomics, yet effectively integrating gene expression, spatial location, and histology remains challenging. We present STESH, a Spatial Transcriptomics clustering method that combines Expression, Spatial information and Histology. STESH extracts histological features using a convolutional neural network and generates expression, histology, spatial, and collaborative convolution modules for a multi-view graph convolutional network with a decoder and attention mechanism. We evaluated STESH on multiple tissue types and technology platforms. STESH consistently outperformed ten state-of-the-art methods, achieving superior clustering accuracy with the highest scores in adjusted Rand index, normalized mutual information, and Fowlkes-Mallows index.

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Zhang, H., Chang, J., Sun, Y., Hu, P., Liu, J., Luo, J., Yang, H., Ren, Y., Zhang, X., Chen, Z., Wong, K. W., Shao, H.. 2025-10-24. Histology-informed spatial domain identification through multi-view graph convolutional networks. https://doi.org/10.1101/2025.10.23.683862

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