Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation

• DOI: 10.2196/19879
• Publication Date: 2020-10-07T14:30:24Z
• Authors: Julian Gruendner; Nicolas Wolf; Lars Tögel; Florian Haller; Hans-Ulrich Prokosch; Jan Christoph
• Keywords: Identification

Background The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for identification and evaluation driver mutations defining personalized treatment regimens. meaningful combination omics data, ie, pathogenic gene variants alterations with other patient understand full picture malignancy been challenging. Objective This study describes implementation a system capable processing, analyzing, subsequently combining NGS clinical analysis within across institutions. Methods On basis already existing workflows malignant at Institute Pathology University Hospital Erlangen, we defined basic requirements on processing pipeline implemented based GEMINI (GEnome MINIng) open source genetic variation database. For purpose validation, this was applied from 1000 Genomes Project derived 206 patients local hospital. We further integrated structures integration centers Erlangen combined nongenomic patient-derived Fast Healthcare Interoperability Resources format. Results Using cohort as input, produced same results established methodologies. Further, it satisfied all our identified successfully infrastructure. Finally, showed exemplary how could be quickly loaded analyzed KETOS, web-based platform statistical decision support. Conclusions demonstrates that database can augmented create pipeline. generates high-quality consistent variant annotation pathological evaluation. demonstrate NGS-derived genomic analysis, thereby providing using standardized vocabularies methods. feasibility hospital by center infrastructure, which is currently being Germany.