CLC bio Reveals Genomics Gateway - A Genome Informatics Framework

Today at the Copenhagenomics conference, CLC bio has revealed Genomics Gateway - a new framework for visualizing, combining and analyzing genome data. The first version focuses on comparative filtering of genomic variations, giving scientists a fast and easy way to do functional classification and filtering of SNPs or other kind of genomic variations, using multiple data sources, including external public databases. This framework offers users a fast and easy way to do further downstream analyses and to combine them with existing knowledge.

Director of Scientific Software Solutions at CLC bio, Dr. Roald Forsberg, states, "This year marks the 10th anniversary of the Human Genome Project. Over these 10 years, we have seen fantastic developments in genome biology based on this remarkable achievement. However, genome informatics is still lacking behind the biological discoveries especially since the advent of next generation DNA sequencing. That’s why we have built the Genomics Gateway framework which enables bench scientists as well as bioinformatics developers to access powerful tools to visualize, combine and analyze genomic data from their own experiments and existing data sources. We envision that the Genomics Gateway will provide an integrated and user-friendly framework for genome science efforts such as functional genomics, systems biology, medical genetics and population genetics, allowing our users to truly realize the potential and promise of the human genome effort."

Bioinformatics Specialist at CLC bio, Dr. Anika Joecker, elaborates, "As an example, you can compare genomic variations like SNPs in cancer samples with somatic or common genomic variants in various well curated public databases like COSMIC and dbSNP. By using different kind of refiners in Genomics Gateway, you can easily compare and filter different information tracks to identify somatic mutations, which play a role in cancer development or drug resistance. Genomics Gateway can save considerable time in the data analysis step!"