Poster Presentation Multi-Omics Conference 2024

The biological mechanisms behind the survival of cancer cells and treatment response are very complex and yet to be understood. Tackling this research problem, my new software tool, IRIS, provides a novel means of analysing and integrating multiomic data. IRIS, standing for Integrative Region Indexing System, has been instrumental in detecting treatment response in tumour models, where the more widely used analysis methods struggled to extract meaningful data. IRIS has revealed new gene sets, genomic regions of interest, and trends in the data distribution that add greater context to the action of therapeutic agents. The key data analysis principles applied by IRIS include:

1. Using highly interpretable statistical metrics to process data (e.g. correlation analysis, principal component analysis, data density and data distribution metrics)
2. Taking into account genomic locations of the features of interest, thus defining the scope of statistical tests, making them region-specific
3. Preserving all data points with minimal filtering so as to not lose valuable information

IRIS features an intuitive graphical user interface (GUI), multiprocessing algorithms allowing for fast computationally intensive analysis, as well as data visualisation frameworks with an in-built data browser based on the Circos tool. All of these features contribute to making IRIS a powerful and effective software program for multiomic data analysis and exploration, which can be used by biologists without any prior programming knowledge.