Bioinformatics analysis tailored to answer your research question.
We apply best-practice analysis methodology for testing hypotheses or exploring large data sets, and even develop new methods if needed. Next-generation sequencing data is the focus in the most of our projects, but we do also encounter other biological data types all the time.
Due to our broad experience in working with various research groups and companies, it is more likely than not that we are familiar with your research topic and the best approaches to get most out of your data.
Identify and understand genomic variation and mutations.
Whole-genome, whole-exome and targeted sequencing allows mapping and studying genetic variants or mutations. Our genome variation analysis identifies SNPs, indels, gene copy numbers, and genomic rearrangements from the various types of DNA-sequencing and microarray data.
Annotating the variants with allele frequencies in public domain databases, pathogenicity predictions and known clinical associations allows focusing on the variants that matter. Tailored downstream bioinformatics analysis of variants and mutations coupled with phenotypic data enables the discovery of novel associations.
For non-model organisms, we produce annotated genome assemblies with computational post-processing steps to ensure the best possible starting point for future studies.
Uncover differences in gene expression and pathways.
Transcriptomics refers to the study of gene expression both on the level of single genes and pathways. Bioinformatics analysis of RNA-sequencing or expression microarray data allow pinpointing molecular mechanisms between the genotype and phenotype. Special question in the field involve — among others — fusion genes, lncRNAs, microRNAs, and alternative splice patterns.
For non-model organisms, RNA-seq data offer significant benefits in assembling genomes as well as naturally assembling and annotating entire transcriptomes. High-quality gene models then enable expression studies just like in a model organism.
Combine your data with public resources and bioinformatics analysis to understand gene regulation deeper.
Epigenomics aims at mapping the dynamic state of the DNA. This means segments of open chromatin, histone locations, methylated CpG islands or binding sites of transcription factors in promoters and enhancers, for example. Our bioinformatics analysis of the various epigenomic NGS data allow associating the identified genomic sites to phenotypic attributes. Furthermore, the sites can be annotated with public domain database information to help in interpreting the biological meaning of these events.
Discover unexpected insights in large data sets.
Statistical bioinformatics analysis can be applied to any biological data. In addition to individual data sources, integration of multiple data types allows access to knowledge that would be impossible to gather from any one type of data alone.
Further, our data management solutions enable secure storage, flexible databases as well as facilitate easy interpretation and data sharing using interactive web-based visualization methods.
How do you wrap up these bioinformatics analysis as a service?
Besides the actual bioinformatics analysis, our service is about continuous support, communication, and making discoveries together.
You can work with our team in the planning phase, active research phase, as well as the publication phase. Consulting projects help you get started, research projects aim at generating, analyzig and publishing NGS data, and software projects result in bioinformatics analysis and dissemination tools, such as automatic pipelices and web applications. Take a look at our service page to read more.