MOLGENIS
MOLGENIS federated data infrastructure
MOLGENIS is a virtual data infrastructure for large (inter)national multi-centre health research communities, such as current partnerships around population cohorts, genetics/genomics, environmental factors, rare diseases and cancer. MOLGENIS provides these communities with user-friendly software, professional support and secure hosting to accelerate their research lifecycle, such as catalogues for reusable data discovery and access requesting, portals for data queries and interpretation, best-practice analysis pipelines, large-scale data storage, HPC computing, and data archiving. MOLGENIS is open access (partnership/fee-based) and all tools are free and open source, implementing (inter)national standards and FAIR principles, so they can easily be reused.
Infrastructure and User Services
Examples of EU level data collections:
- EU Health research data & samples catalogue (900+ collections)
- EU Child Network (multi-center cohort studies on child development)
- European Human Exposome Network (multi-center studies on environment and health)
- BBMRI-ERIC biobank directory (470+ biobanks)
- ERN SKIN (skin disease)
- ERN CRANIO (craniofacial anomalies and ear, nose and throat disorders)
- ERN GENTURIS (heritable cancer)
- ERN ITHACA (Intellectual development disorders)
- ERN ReCONNET (Connective Tissue and Musculoskeletal disorders)
- Solve-RD/ERDERA (massive 19,000+ patients rare disease study)
- Various specific databases (e.g. arvc, deb-central, etc)
- EUCAIM imaging data catalogue
Examples of NL level data collections:
- Lifelines data catalogue
- UMCG cohort catalogue
- AUMC cohort catalogue
- UMCU cohort catalogue
- Maastricht cohort catalogue
- KWF NESTOR (heritable cancer)
- KWF FORCE (rare cancer)
- PALGA openbare databank (pathology samples)
- FAIR genomes network (collaborating genetics and pathology departments of dutch UMCs)
- VKGL variant database (society of Dutch diagnostic labs)
- Various study specific databases (e.g. OA-Trialbank, 1000IBD)
Services:
- Application/database server cloud (100+ instances)
- HPC / AI platform (800+core, 8GPU, 1500TB storage)
- International network of DataSHIELD and MOLGENIS installations (26 countries, 100+ institutes)
- Catalogue platform (using MOLGENIS catalogue)
- Data repository platform (using MOLGENIS EMX2 data platform)
- Federated analysis platform (using Armadillo and DataSHIELD)
- Rare disease genomics workflows (e.g. VIP analysis pipeline)
- Authorization/Authentication (using SURF SRAF or EU Lifescience AAI)
- Genomics pipeline (link to X-omics)
Examples/description of the type of research ?
Studying the interactions between environmental, lifestyle and biological factors to determine people’s risks of developing cardiometabolic non-communicable disease. (LongITools)
Solve unsolved rare diseases through massive data re-analysis of 10,000-100.00 unsolved rare disease patients and novel combined -omics approaches (Solve-RD and ERDERA)
Determine whether cancer has a hereditary cause and the effects of prevention or early detection by generating a large database of individuals with a proven hereditary predisposition to cancer (NESTOR).
Launching Europe’s first-ever trial using biomarkers aimed at preventing the symptomatic onset of the disease before it even begins, and ultimately, transform Crohn’s Disease from an incurable condition to one that can be effectively managed and potentially halted before it even starts (INTERCEPT)
Determine which new disease genes can be uncovered through associative analyses on many genomes with the same or similar disease phenotypes. Assess whether AI models can provide more accurate predictions for our patients when using Dutch reference genomes. Discover pharmacogenomic associations for better personalised treatment. (FAIR GENOMES)
Enable research to better prevent, predict, diagnose and treat disease, using a large, multigenerational cohort study that includes over 167,000 participants (10%) from the northern population of the Netherlands (Lifelines)
Scaling-up to study multimorbidity in the Dutch context using deep-phenotyping data, both clinical and biomedical, among >500.000 individuals, which facilitates (epidemiological) research into the prevention, etiology and course of chronic non-communicable diseases.. (Netherlands Cohort Consortium)
How to access the infrastructure
80% virtual access via web
Public access via web user interface. Password controlled access via web user interface. Access via programmatic interfaces for data queries, submitting updates
20% remote access into facilities
Access via programmatic interfaces for remote access/analysis (e.g. datashield, beacon protocols). Access via login into high performance computing