Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics
Bienroth, D.; Charitakis, N.; Jaeger-Honz, S.; Garkov, D.; Elliot, D.; Porrello, E. R.; Klein, K.; Nim, H. T.; Schreiber, F.; Ramialison, M.
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The field of spatial transcriptomics is rapidly evolving, with increasing sample complexity, resolution, and tissue size. Yet the field lacks comprehensive solutions for automated integration and analysis of multi-slice data in either stacked (3D) or co-planar (2D) formation. To address this, we developed VR-Omics, a free, platform-agnostic software that distinctively provides end-to-end automated processing of multi-slice data through a biologist-friendly interface. Benchmarking against existing methods demonstrates VR-Omics unique strengths to perform comprehensive end-to-end analysis of multi-slice stacked data. Applied to rare paediatric cardiac rhabdomyomas, VR-Omics uncovered previously undetected dysregulated metabolic networks through co-planar slice analysis, demonstrating its potential for biological discoveries.
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