2.2 Comparative and integrative analysis of 'omics' data.

Responsible: Benedikt Brors, DKFZ, Heidelberg.

Background:

One of the strengths of the NGFN2 approach is the diversity of data-types that are being generated in numerous disease areas. These include the abundance of molecules or transcriptional units, as well as mutations either on genomic/transcriptomic or transcriptomic/proteomic levels. Despite the fact that additional high-value knowledge could be gained by integrating all available data in an analysis, efficient methods for such analyses are still not available. This sub-project intends to fill this gap by systematically comparing data on all three levels. We will study their particular strengths and weaknesses, and develop methods for the simultaneous assessment especially in terms of their associations with disease phenotypes.

Planned Work:

We will systematically explore concordance as well as discrepancies between data investigating genomic, proteomic and transcriptomic changes in samples of diseased tissue, and develop methods for integrating them simultaneously into analyses. In particular, we will:

• Check for correlations among proteomic and transcriptomic data.
• Develop means for integrating heterogeneous data into a single analysis.
• Develop consistency checks for the data during integration.
• Develop methods to predict genomic changes from transcriptomic analyses.
• Conduct a prototypic analysis on a complete vertical 'omics' data set.