MultiSight introduces an innovative approach to multi-omics data integration. In the exploration of various integration tools, the project leverages the diversity across multiple methods tailored for specific data combinations and omics levels. Through systematic evaluations and comparisons, it contributes to the advancement of biological interpretation of multi-omics datasets, offering a balanced and effective solution for diverse experimental settings and data types. The developed procedures help with the future research in integrating novel omics technologies, such as time-course single-cell and spatial-omics. Thus, the project lays the groundwork for new research directions and discoveries in the dynamic realm of multi-dimensional data analysis.
Objectives
1. Developing multi-omics benchmarking datasets
2. Benchmarking approaches for various combinations of multi-omics (sub)sets
3. Biological evaluation of the models within developed framework
The project received funding as a post-doctoral project by the Slovenian Research and Innovation Agency (ARIS).
Duration: 1.1.2025 – 31.12.2026