Thor: a platform for cell-level investigation of spatial transcriptomics and histology
Pengzhi Zhang, Weiqing Chen, Tu Tran, Minghao Zhou, K. Carter, Ibrahem Kandel, Shengyu Li, Xen Ping Hoi, Yuxing Sun, Li Lai, Keith A. Youker, Qianqian Song, Yu Yang, Fotis Nikolos, Zejuan Li, Keith Syson Chan, John P. Cooke, Guangyu Wang
Abstract
Spatial transcriptomics links gene expression with tissue morphology, however, current tools often prioritize genomic analysis, lacking integrated image interpretation. To address this, we present Thor, a comprehensive platform for cell-level analysis of spatial transcriptomics and histological images. Thor employs an anti-shrinking Markov diffusion method to infer single-cell spatial transcriptome from spot-level data, effectively combining gene expression and cell morphology. The platform includes 10 modular tools for genomic and image-based analysis, and is paired with Mjolnir, a web-based interface for interactive exploration of gigapixel images. Thor is validated on simulated data and multiple spatial platforms (ISH, MERFISH, Xenium, Stereo-seq). Thor characterizes regenerative signatures in heart failure, screens breast cancer hallmarks, resolves fine layers in mouse olfactory bulb, and annotates fibrotic heart tissue. In high-resolution Visium HD data, it enhances spatial gene patterns aligned with histology. By bridging transcriptomic and histological analysis, Thor enables holistic tissue interpretation in spatial biology.