Abstract
One child in every 200 births may be affected by one of the approximately 6,000 monogenic diseases discovered so far. Establishing the pathogenicity of the mutations detected with NGS (Next-Generation Sequencing) techniques, within the sequence of the associated genes, will allow Precision Medicine concept to be developed. However, sometimes the clinical significance of the mutations detected in a genome may be uncertain (VUS, Variant of Uncertain Significance) which prevents the development of health measures devoted to personalize individuals' treatments. A VUS pathogenicity can be inferred thanks to evidences obtained from specific types of NGS studies. Therefore the union of supercomputing through HPC (High-Performance Computing) tools and the cloud computing paradigm (HPCC), within a Data Center federation environment offers a solution to develop and provide services to infer the pathogenicity of a set of VUS detected in a genome, while guaranteeing both the security of the information generated during the whole workflow and its availability.
Highlights
The progress of healthcare research has always been one of the main challenges facing humanity
Significant efforts have been made to characterize the clinical significance of a variants of uncertain significance (VUS), there is a lack in the adoption of new paradigms which focus in the integration of -omics1 data sets all of which would be useful to improve the pathogenicity prediction of a VUS and to identify the function of the genes involved in the development of hereditary diseases
The contribution of our work is to demonstrate how the union of supercomputing and the cloud computing paradigm, within a Data Center federation environment, can generally be useful to improve the provision of services which are able to meet users’ demands
Summary
The progress of healthcare research has always been one of the main challenges facing humanity. A key challenge is that the clinical significance of a VUS result for disease risk is in principle unknown In this sense, significant efforts have been made to characterize the clinical significance of a VUS, there is a lack in the adoption of new paradigms which focus in the integration of -omics data sets all of which would be useful to improve the pathogenicity prediction of a VUS and to identify the function of the genes involved in the development of hereditary diseases. The contribution of our work is to demonstrate how the union of supercomputing and the cloud computing paradigm, within a Data Center federation environment, can generally be useful to improve the provision of services which are able to meet users’ demands. The paper finishes with our conclusions and a description of future areas of research
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