Project Details
Projekt
INF: Data management, bioinformatics and statistics for metagenome analyses
Subject Area
Gastroenterology
Term
since 2020
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 426660215
The INF project from phase 1 (PIs Prof. Astrid Dempfle and Prof. David Ellinghaus) is the central data management and analysis project of miTarget and covers three essential work packages (WPs): data management (WP1), bioinformatic pipeline development (WP2), and statistics (WP3). In Phase II, we will, among other things, expand data management functionalities in terms of automated metadata information retrieval, high-performance (web)calculations and synchronisation, and introduce new training capabilities and the use of federated learning apps (WP1). We will further develop advanced bioinformatics pipelines for the analysis of dark matter (disease-relevant “bioactive” and often uncharacterized) gene products and modules and their associations with phenotypic information (via prioritisation scores), in combination with metatranscriptome expression data, and the detection of viruses and phages (WP2). In WP3, we will establish privacy-compliant, ultra-fast and user-friendly bioinformatics web services for our most used pipeline applications, GPU-accelerated deep learning for metagenomic binning and computation of host-genetic polygenic risk scores (PRS) and polygenic microbiome risk scores (mPRS). In the statistics work packages, we will establish and develop further statistical methods for network analysis of microbiome data with particular focus on integration of multi-omics data, identification of key constituents and a core microbiome and network-construction for genetically related individuals in family studies (WP4). In addition, we will provide the consortium with expertise and statistical methods for interventional trials (RCTs) with the microbiome as a therapeutic target (WP5) and again offer central statistical support and collaboration with all partners in the RU (WP6).
DFG Programme
Research Units
