We provide tailored bioinformatics data analysis service for industry, academia and private customers. net-OMICS main focus is integrative systems-level network-based single or multi-OMICS data analysis (i.e. Integromics), linking together different layers of regulatory data (e.g. DNA variation, transcription profiles, protein or metabolite levels) into biologically or clinically meaningful network models. By this, we aim to assist life scientists in novel biomarker, candidate gene or drug target discovery, data interpretation, as well as experimentally testable hypothesis generation.

However, we can also perform the pre-processing steps (i.e. quality control, filtering, read mapping, normalization, differential expression analyses, SNP/indel mapping) when starting from raw NGS or array-based Genomics, Transcriptomics or other `OMICS' data.

On request, we can do client-tailored custom scripting and develop customized analysis pipelines for particular research topics of interest and data sets at hand (i.e. beyond genome and transcriptome data).


We offer genotyping array and exome sequencing (Exome-seq) data analysis, including quality control and data cleaning, SNP/indel calling and functional annotation, adjustment for confounders, imputation, association analysis and visualization.


We offer RNA-seq, microarray and RT-qPCR data analysis, including quality control, data filtering, normalization, differential expression analysis and visualization. Both protein coding and non-coding RNA transcripts can be analyzed at gene or isoform-level.


Our main focus is integrative systems-level network-based single and multi-OMICS data analysis, starting from pair-wise integrations, e.g. via quantitative trait loci (QTL) mapping, linking DNA variation to transcript, protein or metabolite levels, to multi-level network and pathway analysis, resulting in biomarker selection, biological hypothesis generation and insightful data interpretation.