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SPEX: A modular end-to-end analytics tool for spatially resolved omics of tissues

Ximo Pechuan Jorge, Xiao Li, Tyler Risom, Artem Zubkov, Evgeniy Tabatsky, Aleksandr Prilipko, Xin Ye, Zhen Shi, malgorzata Nowicka, Frank Peale, Derrek Hibar, James Ziai, Raj Jesudason, Darya Orlova
bioRxiv (2022)

Abstract:

Recent advancements in transcriptomics and proteomics have opened the possibility for spatially resolved molecular characterization of tissue architecture with the promise of enabling a deeper understanding of tissue biology in either homeostasis or disease. The wealth of data generated by these technologies has recently driven the development of computational pipelines that, nevertheless, have the requirement of coding fluency to be applied. To remove this hurdle, we present SPEX (Spatial Expression Explorer), a comprehensive image analysis software implemented as a user-friendly web-based application with modules that can be put together by the user as pipelines conveniently through a graphical user interface. SPEX’s infrastructure allows for streamlined access to open source image data management systems and analysis modules for cell segmentation, cell phenotyping, cell-cell co-occurrence and spatially informed omics analyses. We demonstrate SPEX’s ability to facilitate the discovery of biological insights in spatially resolved omics datasets from healthy tissue to tumor samples.

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