Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study

    November 2022 in “ bioRxiv (Cold Spring Harbor Laboratory) ”
    Michael Fatemi, Eric Feng, Cyril Sharma, Zarif Azher, Tarushii Goel, Ojas A. Ramwala, Scott Palisoul, Rachael E. Barney, Laurent Perreard, Fred Kolling, Lucas A. Salas, Brock C. Christensen, Gregory J. Tsongalis, Louis Vaickus, Joshua Levy
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    Preprint — not peer reviewed. This was posted to a preprint server or data repository. It has not been through a journal's review process, and its findings may change or not hold up.

    Studysummary In this study, deep learning models accurately predicted gene expression in whole slide images of colorectal cancer, with convolutional neural networks outperforming transformer and graph-based approaches in spatial RNA pattern prediction.
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