DC 5 - Multi-omics: building and curating a community database and constructing complex data analysis models

• Objectives:

Aim of the project. To create a comprehensive database by compiling data from all consortium partners and incorporating it into the network. These datasets will be combined and curated for quality, matched with possible metadata, and prepared for merging and future use by researchers or larger meta multi-omic studies

1. Combine the datasets (metabolomic / lipidomic, transcriptomic, genomic, etc) generated by consortium into one curated database for adaptive and innate immunity research.
2. Develop computational, statistical and machine learning tissue-specific techniques for processing of qualitative and quantitative multiomics data.

• Brief project description:

Recent advancements in multi-omics have led to significant discoveries in immunology, but the access to and integration of different types of omics data remains limited. Most databases focus on single omics layers (e.g., metabolomics, genomics, or transcriptomics), which makes it difficult to conduct comprehensive analyses across multiple biological dimensions. In addition, while many researchers generate various datasets, access to them is often limited and widely scattered. We aim to create a novel, immunology-specific database using the network’s data, which will provide greater statistical power and a more comprehensive understanding of immunological responses and tolerance. This will enable consortium partners to gain deeper insights from their results.

As a next step, the models created will be trained on this unique rich big dataset, generated by different research groups and specific immunological viewpoints. No such models exist to our knowledge. These models will empower the researchers within and beyond the field.

• Planned secondments:

1. Limonciel lab (Biocrates, Autria), M19-20, Learn the process of how data is generated and processed before the data reaches the data analysis stage.
2. Everts lab (Leiden University Medical Center, The Netherlands)Learn the specifics of microbial (spatial) metabolites and what aspects need to be addressed  by computational analyses