Understand disease etiology and phenotypes through genomic variation and mutations.
Whole-genome, whole-exome and targeted DNA sequencing allows identifying 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 population allele frequencies, pathogenicity predictions and known clinical associations allows us to focus on the variants that matter. Tailored downstream bioinformatics analysis of variants together with phenotypic data enables the discovery of novel associations and biomarkers.
For microbes and non-model organisms, we produce annotated, quality-controlled genome assemblies in order 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 on the level of genes and pathways. Bioinformatics analysis of RNA-sequencing or single-cell RNA-sequencing data allows pinpointing molecular mechanisms between the genotype and phenotype. Special questions in the field include microRNAs, lncRNAs, fusion genes and alternative splice patterns.
For microbes and non-model organisms, we produce annotated, quality-controlled transcriptome assemblies in order to ensure the best possible starting point for future studies.
Combine your data with public resources and bioinformatics analyses for a deeper understanding of gene regulation.
Epigenomics aims at mapping the dynamic state of the DNA. This may mean segments of open chromatin, histone locations, methylated CpG islands or binding sites of transcription factors in promoters and enhancers, for example. Our bioinformatics analyses of epigenomic NGS data allow association of the identified genomic sites to phenotypic attributes. Furthermore, the sites can be annotated with public domain database information in order to help interpret the biological meaning of these events.
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