Wings: Widely Integrated Federated Platform For Analyzing Whole

Background and aim: genomic medicine is currently the main component of personalized medicine. this rapidly developing science-driven approach to healthcare holds great benefits for patients, clinicians, healthcare providers and society as a whole. it promises to change healthcare from being reactive to disease to being predictive to disease onset, from being general for all to being tailored to the individual. health will become personalized and will change from cure to prevention, partly by avoiding severe, genetic disorders. this new approach towards the use of genomic information is highly disruptive to current medical procedures, to the it infrastructure used in medicine, and towards the role of genetic specialists in medical organizations. the main bottleneck for the biomedical use of next-generation sequencing is the medical interpretation of large-scale genomic data. thus, to maximize the potential of genomic medicine we have to: a. improve genome-wide genetic analysis and diagnostic strategies. b. investigate the infrastructure and strategies to detect, store and report findings from genomic information to patients. c.explore the feasibility of integrating medically actionable genomic variants, including carrier status, into the health care system. d. develop strategies for genomic data sharing to foster a learning health environment. methods: wings is aimed at breaking down the complexity of analyzing genome sequencing data. it uses a federated data model to optimize ict requirements of whole genome sequencing (wgs) interpretation. both genotype and phenotype data of individuals are kept locally, at the geographically distributed genomic centres, to ensure data protection. to facilitate setup, locale data stores are provided as a containerized module including the nosql database and all required communication routines. centralized access through the wings online interface is managed through access control lists, allowing cross-centre collaboration and meta-analysis. results: wigs has been installed in several hospitals and clinics in belgium. conclusion: in wings federated analysis is applied to handle the balance of data confidentiality and data analysis from a technical perspective and leverage genome interpretation by sharing genomic information. we developed a tool to add phenotypic information to the patient profile. moreover, it possible to identify an association between variants and phenotypes. eventually, such associations can be further ranked based on functional data using prioritization methods, such as extasy and eximiser.