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.

doi:10.1101/2023.03.31.535025

bioRxiv · 10.1101/2023.03.31.535025

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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Abstract

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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Bienroth, D., Charitakis, N., Jaeger-Honz, S., Garkov, D., Elliot, D., Porrello, E. R., Klein, K., Nim, H. T., Schreiber, F., Ramialison, M.. 2023-04-02. Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics. https://doi.org/10.1101/2023.03.31.535025

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