Our GWAS-MAP platform integrates results of genome-wide association and functional genomic analyses of millions of samples. With these big data, we apply novel analytical methods to develop etiologic hypotheses, discover candidate risk assessment biomarker, and biomarkers that may help stratifying the patients into different molecular subtypes of disease.

Science lies at the heart of PolyKnomics. For example, we are currently involved in two omics-related EU FP7 projects. For private customers we offer various solutions ranging from “you bring the samples, we will report the findings” to advice on how improve their experiments or analyses.

With the ever growing amount of data in the life sciences, proper data management according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles is of paramount importance.

It is not uncommon that people spend millions of euros on experimental, functional, and clinical follow-up of some findings only to discover that they are chasing false-positives which resulted from e.g. a bug in the statistical quality control procedure. And we all know that having original work published in Science or Nature does not guarantee that reported results are reproducible. We can help you with establishing reproducible research pipelines or with a ‘scientific audit’ before you invest follow-up of some previous (external) work.

Modern science is nowhere without software. We develop new solutions or tailor existing ones to your needs. Keywords are free/open source software, R, C++, Python.

Thinking about setting up a new compute cluster for your omics analysis? Having trouble keeping your Linux systems up to date? Let us help! We have several years of experience in design and maintenance of small to medium sized compute/storage clusters for research use.