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Pediatric rhabdomyosarcoma: multimodal genomic and clinical analysis

How MediVerse integrates gene expression and clinical data in a single voice-driven workspace.

Overview

This case study highlights how MediVerse's voice-driven VR interface enables sophisticated multimodal analysis of pediatric rhabdomyosarcoma (RMS) by integrating genomic and clinical data seamlessly, without SQL or manual navigation. Imported datasets include the gene expression intensity matrix and SVD results.

Workflow

  1. Initial scatter by histology. Voice command: "Show a 3D scatter of V1, V2, V3 coloured by histology."
3D scatter plot of spatial data by histology
Fig. 5. Initial 3D scatter plot coloured by histology.
  1. ERMS samples only. "Show a 3D scatter of V1, V2, V3 for ERMS samples only, coloured by histology."
3D scatter of ERMS samples coloured by histology
Fig. 6. ERMS samples scatter coloured by histology.
  1. Colour by age status. "Show a 3D scatter of V1, V2, V3 for ERMS samples only, coloured by AgeStatus."
3D scatter of ERMS samples coloured by age status
Fig. 7. ERMS samples scatter coloured by AgeStatus.
  1. High-risk ERMS patients. "List all ERMS patients with AgeStatus equal to Unfavourable and survival_time less than 2 years."
Table of high-risk ERMS patients
Fig. 8. Table of high-risk ERMS patients.
  1. PAX3 expression line chart. "Show a line chart of expression values across all samples for pax3."
Line chart of PAX3 expression across all samples
Fig. 9. PAX3 expression across all samples.

Results & impact

MediVerse enables intuitive, natural-language-driven exploration of integrated genomic and clinical datasets in VR. Researchers can uncover relationships between histological subtypes, prognostic age groups, and gene expression patterns, all within an immersive environment.