Many diseases, including cancer, remain difficult to fully understand because researchers have often had to study cells outside of their natural environment. This means missing vital clues about how cells interact and behave in real tissues. Spatial transcriptomics (ST) is a breakthrough technology that allows to map which genes are active in each cell directly within intact tissue, preserving their natural “neighbourhoods.”
While ST opens an entirely new window into biology, the data it produces is incredibly complex. That’s where VR-Omics comes in: an interactive, user-friendly tool we developed to transform ST data into detailed 3D maps that researchers can explore. With VR-Omics, scientists can step “inside” tissues, view patterns of gene activity from the cells’ own perspective, and uncover insights that might otherwise be missed. By removing the need for advanced computational skills and providing an end-to-end analysis pipeline, VR-Omics speeds up the journey from data to discovery. Our ultimate aim is to help researchers everywhere explore tissue architecture in detail, leading to deeper biological understanding and faster medical breakthroughs.
Impact
VR-Omics has already led to important new findings, such as identifying previously unseen patterns in a rare childhood heart muscle cancer. It’s now being used across our institute to study a wide range of topics, from developmental disorders and stem cell models to different cancer types. By making complex tissue data easy to navigate, VR-Omics helps scientists work faster, uncover hidden details, and develop better approaches for diagnosing and treating disease. This offers hope for improved patient outcomes in the future.
reNEW research
The VR-Omics tool is already fully operational and supports data from multiple leading ST technologies. Our work has been published in Genome Biology and the tool is freely available for researchers worldwide. We continue to refine and expand VR-Omics, adding new features and improving usability so more scientists can benefit from it.
Image description
This vibrant 3D image shows clusters of cells within breast cancer tissue. Each cluster is colour-coded by its unique gene activity pattern, revealing how the tumour is made up of many different parts. By studying this cellular “map,” researchers can better understand how cancers grow and adapt. This is crucial knowledge that could guide the development of more targeted treatments.
Credits
Denis Bienroth, Software Engineer, Ramialison Lab, reNEW Melbourne.
