The emergence of the high-throughput next generation sequencing (NGS) technologies has led to the combined analysis of cancer with multi-dimensional molecular data, such as DNA-copy number alteration, mRNA and protein expression. The combination of genomic, metabolomic and clinical data on studying many types of solid cancers are emerging and play an important role in discovering novel biomarkers, and identifying patient subgroups for tailored therapy and personalized treatment. Integrative Genomics study is a range of methodologies that can be used to interpret the combination of molecular biomarkers identified at the DNA, mRNA, microRNA and proteins levels in cancer research. It requires expertise in different disciplines in biology, medicine, mathematics, statistics and bioinformatics.
Quick Biology's advanced service in Integrative Genomics can provide you expertise in analyzing and interpreting these combined NGS data. We can provide the following benefits:
1. Sequential analysis combining several distinct omics data from same set of samples.
2. Penalized likelihood analysis to handle high-dimensional multi-omics data.
3. Gene-set analysis to discover novel or using known groups of related genes/molecules.
4. Pairwise correlation analysis to infer molecular network interactions.
5. Network analysis using molecular network interactions to identify active or aberrant subgraphs.
6. Bayesian analysis to guide making correct assumptions to integrate multiple omics data.
7. Integrative analyses of many tumor types for clinical application.