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Complex chronic diseases are usually polygenic, heterogeneous and have highly interrelated networks of metabolic processes. Multiple factors (including maybe 5 or 10 genes and many non-genomic factors such as co-morbidities, assay results, treatment history & environment) act in combination to determine the disease risk. Identifying clinically relevant networks of multi-modal biomarkers associated with specific outcomes, e.g. disease risk or therapy response,  is hugely complex.

This talk will describe a new platform (Synomics) that enables very rapid discovery and validation of multi-omics biomarker networks, associating up to 30 features in combination across the largest genomics and clinical studies of complex diseases. An example association analysis of a breast cancer population of 14,777 people, all of whom had BRCA1 and/or BRCA2 mutations will be described. The most complex biomarker networks identified, with high clinical penetrance, contain 17 SNPs acting in combination. These results were found and validated in 6 days on a single 4 GPU POWER8 server.

Date: September 12th, 9:00am (BST) and 4:00pm (BST)

Free registration: https://register.gotowebinar.com/rt/3729993526848725762