Version 1 (modified by rick, 8 years ago) (diff)



The mission of the BIOS Consortium is to create a large-scale data infrastructure and to bring together BBMRI researchers focusing on integrative omics studies in Dutch Biobanks.
The advent of the genome-wide association study (GWAS) led to the successful identification of thousands of variants that are robustly associated with complex disease phenotypes. Dutch biobanks played a substantial role in these discoveries. For most of these variants, however, the mechanisms through which they contribute to these phenotypes remain unknown. The BIOS Consortium applies a functional genomics approach that integrates genome-wide genetic data with data on the epigenome and transcriptome to elucidate these mechanisms. Over 4000 samples from BBMRI-NL biobanks with in-depth information on disease phenotypes and GWAS data have been enriched with RNA-sequencing (>15 M paired end reads) and genome-wide DNA methylation data (Illumina 450k arrays). The same is true for samples with whole-genome sequencing data from GoNL. This unique data infrastructure provides a powerful platform to evaluate key questions in integrative omics from establishing comprehensive eQTL and meQTL catalogues to linking molecular pathways across omics levels to phenotypic outcomes.

Access to BIOS data

There are two ways to access BIOS data:

1. Download of selected data through EGA

RNA-seq, DNA methylation, sex, age and cell count data that has been analyzed in publications can be requested and downloaded from The European Genome-phenome Archive (EGA). The advantage is that data can be downloaded to own computational facilities, but not all data can be accessed (e.g. SNPs). Click here to download the document for BIOS data requests through EGA. The document includes the data sharing policies.

2. Analyze all data on a centralized computational facility

For BBMRI-NL researchers, all data shared by participating biobanks including genome-wide SNP data, limited phenotypes, RNA-seq and DNA methylation on all individuals can be analyzed on centralized computational facilities, namely the LifeScience Grid and the SurfSARA High Performance Computing cloud ( The advantage of this approach is that all available data can be analyzed (including those with a privacy aspect), but the data cannot be downloaded and a relatively strict security protocol has to be adopted. Please, fill out this form if you wish to request access to BIOS data at the SurfSARA servers. To complete this request, you will also need to sign the BIOS Code Of Conduct. Click here for an overview of current data requests.

Publications acknowledging BIOS

Latest update: September 2015

Management team

Bastiaan T. Heijmans (chair)1, Peter A.C. ’t Hoen2, Joyce van Meurs3, Rick Jansen5, Lude Franke6.

Cohort collection

Dorret I. Boomsma7, René Pool7, Jenny van Dongen7, Jouke J. Hottenga7 (Netherlands Twin Register); Marleen MJ van Greevenbroek8, Coen D.A. Stehouwer8, Carla J.H. van der Kallen8, Casper G. Schalkwijk8 (Cohort study on Diabetes and Atherosclerosis Maastricht); Cisca Wijmenga6, Lude Franke6, Sasha Zhernakova6, Ettje F. Tigchelaar6 (LifeLines Deep); P. Eline Slagboom1, Marian Beekman1, Joris Deelen1, Diana van Heemst9 (Leiden Longevity Study); Jan H. Veldink10, Leonard H. van den Berg10(Prospective ALS Study Netherlands); Cornelia M. van Duijn4, Bert A. Hofman11, Aaron Isaacs4, André G. Uitterlinden3 (Rotterdam Study).

Data Generation

Joyce van Meurs (Chair)3, P. Mila Jhamai3, Michael Verbiest3, H. Eka D. Suchiman1, Marijn Verkerk3, Ruud van der Breggen1, Jeroen van Rooij3, Nico Lakenberg1.

Data management and computational infrastructure

Hailiang Mei (Chair)12, Maarten van Iterson1, Michiel van Galen2, Jan Bot13, Dasha V. Zhernakova6, Rick Jansen5, Peter van ’t Hof12, Patrick Deelen6, Irene Nooren13, Peter A.C. ’t Hoen2, Bastiaan T. Heijmans1, Matthijs Moed1.

Data Analysis Group

Lude Franke (Co-Chair)6, Martijn Vermaat2, Dasha V. Zhernakova6, René Luijk1, Marc Jan Bonder6, Maarten van Iterson1, Patrick Deelen6, Freerk van Dijk14, Michiel van Galen2, Wibowo Arindrarto12, Szymon M. Kielbasa15, Morris A. Swertz14, Erik. W van Zwet15, Rick Jansen5, Peter-Bram ’t Hoen (Co-Chair)2, Bastiaan T. Heijmans (Co-Chair)1.

  1. Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
  2. Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
  3. Department of Internal Medicine, ErasmusMC, Rotterdam, The Netherlands
  4. Department of Genetic Epidemiology, ErasmusMC, Rotterdam, The Netherlands
  5. Department of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
  6. Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
  7. Department of Biological Psychology, VU University Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
  8. Department of Internal Medicine and School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands
  9. Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
  10. Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
  11. Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
  12. Sequence Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands
  13. SURFsara, Amsterdam, the Netherlands
  14. Genomics Coordination Center, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
  15. Medical Statistics Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands