INF01 List, Boeker, Schirmer
Integration and analysis of clinical and multi-omics data
Principal Investigators:
List, Markus, TUM
Boeker, Martin, TUM
Schirmer, Melanie, TUM
INF01 is responsible for uniform processing and integration of data across CRC 1371 projects. In the second funding phase, we will extend the existing software platform for processing and integration of metagenomic and metatranscriptomic sequencing data as well as untargeted metabolomics data. We further seek to establish tools for the joint analysis of 16S rRNA and metagenomic sequencing data and a better clinical integration through the development of suitable reporting tools.
INF01 is responsible for developing infrastructure in support of (extended) clinical and research data collection, biosample management as well as translational data analytics and bioinformatics. To this end, we established an integrated platform consisting of four components (Figure)
1. DIS (Data Integration System, developed by bitcare GmbH): a secure platform supporting the collection of (extended) clinical data and patient-reported data as well as the management of well-annotated biosamples from patients relevant to this CRC, e.g. with inflammatory and neoplastic diseases.
2. MSD (Molecular Signatures Database, https://www.misigdb.org/): A microbiome signature database hosting primary human and non-human microbial metabolomic and metagenomic data, also offering analytical pipelines for processing them into signatures and profiles.
3. tranSMART: A translational data warehousing and analytics platform integrating the collected clinical and paraclinical data with associated microbiome profiles and further molecular data, e.g. RNA-seq, to support intuitive querying, data analysis and data visualisation.
4. Namco (https://exbio.wzw.tum.de/namco): A suite of CRC-specific data processing and analysis tools supporting network-enhanced pathway enrichment, biomarker discovery and systems biology-based microbiome signature mining, which will also be integrated into the translational platform.
These components interface through application programming interfaces and allow researchers and clinicians in the CRC to move from data acquisition to data analysis in a user-friendly and seamless fashion.