Genome analysis plays a major role in cancer research. Identifying genetic variations in a person's genome can unearth predisposition to cancer. The cancer genome can provide information about the likely aggressiveness of the cancer or treatment effectiveness against it. Personalizing cancer treatment based on genetic analysis can inform therapy choices and minimize side effects without jeopardizing the success of the treatment. 

Unsurprisingly, studies related to cancer research make up a large proportion of omics data generated - for example 55% of the 7PB of data hosted by EGA are related to cancer studies. Together with rare disease research, cancer research is expected to dominate the data generation in the immediate future. Especially since sequencing methods are advancing at incredible speed and at the same time the costs decrease, leading to increasing cases of routine sequencing for diagnostic purposes.

For these reasons, while engaging and encouraging data submission by researchers in all medical fields, GHGA is initially focussing on cancer and rare disease research to fully address their specific needs. To support these efforts, GHGA will not only accept raw datasets but also generate community reference data collections. Community-specific tailored access portals combined with the curation of reference data collections will ensure the utility of GHGA's datasets to researcher and clinician communities – who in turn will help shape the further development of GHGA.

Here we collected relevant materials for the cancer community, such as highlighting use cases and other news and events.

 

Latest News

New GHGA Podcast episode about patient engagement

Patient involvement can help to focus research and healthcare to the needs of the patients. In this episode Anne Müller relates her experiences in this field.

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Benchmarking genomic variant calling

A recent publication, spearheaded by the Next Generation Sequencing Competence Network (NGS-CN) and GHGA, introduces NCBench, a platform for continuous benchmarking of genomic variant calling workflows.

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Release of the GHGA Metadata Model v1.0 and White Paper

With the refactoring of the GHGA Metadata Model to version 1.0, we released a white paper summarising the development of the model and describing the modelling framework in detail.

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