Array- and sequencing-based genomic technologies allow the simultaneous measurement of millions of molecular variants. The number of applications is gradually growing and includes RNA expression profiling, DNA aberration and methylation detection, mapping of protein binding sites and genotyping. Data analysis is a key step, but few groups have the relevant range of statistics and bioinformatics skills required. Proteomics profiling with microarrays or mass-spectroscopy presents similar challenges. Genomics technologies hold a vast potential to identify biomarkers for diagnosis, prognosis and treatment resistance for personalized medicine. Advanced data analysis methods are required for their application during product development and regulatory decision-making.


  • Statistical consulting
    We provide consultancy services, for the planning, experimental design and analysis of projects, as well as support for grant proposal writing, and consulting services on biostatistics matters. This statistical consulting service is aimed at all persons active in life sciences. It also includes training and teaching, data analysis services, and research collaborations.
  • Education and practical training
    We provide researchers with educational support and practical training in the use of software and analysis methods. This includes the organization of seminars, workshops and training courses.
  • Data analysis services
    We perform computationally intensive analysis using suitably chosen or in-house developed computational tools. We also offer joint analysis of a client’s data with a specifically curated version of publicly available clinical and genomics datasets.
  • Personal embedding
    A data analyst funded by the project is coached by our team members, participates in our meetings, can use the BCF infrastructures and resources and works either at BCF or at the site of the supported group or shares time between the two.


More information about our services and resources


BCF can provide personalized interactive tools for data exploration and analysis. We use for example a combination of R and Shiny software. This screenshot shows an interactive graphic for comparing peak distributions in a pair of ChIPseq samples with added customized annotation tracks not otherwise available. These exploratory tools can be used on the web with a browser.



Pathway analysis: Experimental effects, such as expression levels from MicroArray or RNA-Sequencing data can be visualized in the context of KEGG pathways with components coloured according to user-selected rules.