2023/04/02 by Denis Bienroth, Natalie Charitakis, Dillon Wong +14 · 1 voice
Biochemistry, Genetics and Molecular Biology · #Single-cell and spatial transcriptomics #Renal and related cancers #Cancer Genomics and Diagnostics
paper · pdf · doi:10.1101/2023.03.31.535025
openalex publication_date 2023/04/02 · openalex created_date 2023/04/05 · openalex updated_date 2026/07/15
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.