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Rigor and Reproducibility of Digital Spatial Profiling on Clinically Sourced Human Tissues

Smith, K. D.; MacDonald, J. W.; Li, X.; Beirne, E.; Stewart, G.; Bammler, T. K.; Akilesh, S.

2024-10-18 pathology
10.1101/2024.10.16.618750 bioRxiv
Show abstract

Spatial transcriptomic profiling enables precise quantification of gene expression with simultaneous localization of expression profiles onto tissue structures. This new technology promises to improve our understanding of the disease mechanisms. Therefore, there is intense interest in applying these methods in clinical trials or as laboratory developed tests to aid in diagnosis of disease. Before these technologies can be more broadly deployed in clinical research and diagnostics, it is necessary to thoroughly understand their performance in real world conditions. In this study, we vet technical reproducibility, data normalization methods and assay sensitivity focusing predominantly on one widely used spatial transcriptomic methodology, digital spatial profiling. Using clinically sourced human tissue specimens, we find that digital spatial profiling exhibits high rigor and reproducibility. Our approach lays the foundation for incorporation of digital spatial profiling methods into clinical workflows.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.