Our research focuses on developing VR-Omics, a cutting-edge software designed to simplify spatial transcriptomics analysis. We aim to enable researchers, regardless of their computational expertise, to visualize and interpret spatial gene expression data effectively. This example showcases lung cancer tissue analyzed with VR-Omics. However, VR-Omics is versatile and can handle various types of tissue samples. The software transforms complex datasets into accessible insights, revolutionizing how researchers interact with their data.
Impact
VR-Omics empowers researchers to explore spatial gene expression patterns in a user-friendly virtual reality environment or via a desktop application. This capability can expedite discoveries by allowing users to identify clusters, correlations, and potential markers without needing extensive computational skills. As spatial transcriptomics becomes more prevalent across stem cell research, VR-Omics serves as a crucial tool to enhance the quality and efficiency of data analysis, driving advancements in scientific knowledge and medical research.
reNEW research
The VR-Omics software is fully developed and continuously evolving. We regularly update our workflows and integrate new spatial transcriptomics technologies to ensure researchers have access to the latest analytical tools. We are currently collaborating with a wide range of Labs throughout reNEW to help analysing their spatial data through VR-Omics.
Image description
This image shows a lung cancer tissue section visualized with VR-Omics. The colors represent different gene expression clusters, each indicating specific cellular types and states within the tumor microenvironment. This visualization demonstrates how VR-Omics can uncover critical spatial patterns and interactions in any tissue sample, providing valuable insights into gene expression and cellular organization, and driving advancements in scientific knowledge and medical research.
Credits
Denis Bienroth, Transcriptomics and Bioinformatics Group.
