Integrative Omics data set

The BBMRI-NL Omics data set comprises -omics measures in blood of participants in 29 Dutch cohorts. Genetic, epigenetic, transcriptome and metabolome data are available of approximately 3,500 samples. The BBMRI Omics data set is the joint collection of the GoNL consortium, BIOS Consortium and the Metabolomics Consortium.

What is BBMRI-NL’s Omics data set? 

Use the Explorer to view the data available for analysis.

The BBMRI-Omics data set has been created to study the relations between different omics levels and develop omics signatures of health and disease. The data set is publicly available and has proven to facilitate researchers in their discovery of novel biological mechanisms and biomarkers for health and disease. The BBMRI-Omics data set consists of 3,500 samples with integrative data (genome, epigenome, transcriptome and metabolome) with an extension of the metabolome in 30,000 extra individuals and whole genome sequences of a selective group of 700 individuals. 

The table below shows an overview of the techniques used and number of samples available for the different Omics measures present in the data set.

Omics measure Technique Number of samples
Whole Genome Sequencing Illumina 750
Imputed genotypes HRC ~6000
DNA Methylation Illumina 450K ~4000
Transcriptome Illumina RNA seq ~4000
Metabolome Nightingale NMR ~32,000

        

Why BBMRI-NL’s Omics data set?

With the BBMRI-Omics Explorer, designed to query the Omics dataset, you can explore the number of samples per selected set of omics data types, and check the distribution of sex, age and smoking status of the selected data set. You could also explore the number of individuals with a certain age range of interest having multiple omics levels available.
Intended users
The Omics data set and Explorer are meant for researchers investigating the relation between different genomic levels, and researchers investigating multilevel omics classifiers for disease risk.

Using BBMRI’s Omics data set

All data shared by participating biobanks including genome-wide SNP data, phenotypes, RNA-sequences, DNA methylation, and metabolomics on all individuals can be analyzed on centralized computational facilities, namely a 64-core virtual machine in the SURFsara High Performance Computing cloud. Here, BBMRI-Omics data are readily accessible through the dedicated R package BBMRIomics.

Access to BBMRI-Omics data using a centralized computational facility

In the near future we will have one data access procedure, but currently you still have to follow the separate data access procedures:

Wiki

The BBMRI BIOS consortium has in parallel with the Metabolomics Consortium generated DNA Methylation and Gene expression data. At the wiki, created by the BBMRI BIOS consortium, you can also find all the information concerning data requests, access and processing.

Support for BBMRI-NL’s Omics data set

For support on using the Omics dataset, contact Leon Mei, Molecular Epidemiology, Leiden University Medical Center.

BBMRI-Omics Management Team

Marian Beekman1, Bastiaan T. Heijmans1, Joyce van Meurs2, Lude Franke3, Marleen van Greevenbroek4, Arfan Ikram5, Dorret I. Boomsma6, P. Eline Slagboom1

 

1.Molecular Epidemiology, LUMC, Leiden

2.Internal Medicine, Erasmus University Medical Center, Rotterdam

3.Genetics, University Medical Center Groningen, University of Groningen, Groningen

4.Internal Medicine, School for Cardiovascular Diseases, Fac. Health, Medicine and Life Sciences, Maastricht University, Maastricht

5.Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam

6.Biological Psychology, Vrije Universiteit, Amsterdam