A national platform for clinical genetic analysis of high-throughput sequencing data in Norway. M. C. Eike1, H. Lćrum2, T. Hughes1, S. Bremer3, S. Bergan4, G. Thomassen5, M. Aanestad6, T. Grünfeld1, D. E. Undlien1 1) Department of Medical Genetics, Oslo University Hospital, University of Oslo, Oslo, Norway; 2) IT Department, Oslo University Hospital, Oslo, Norway; 3) Department of Medical Biochemistry, Oslo University Hospital, Oslo, Norway; 4) Department of Pharmacology, Oslo University Hospital, Oslo, Norway; 5) University Center for Information Technology (UCIT), University of Oslo, Oslo, Norway; 6) Department of Informatics, University of Oslo, Oslo, Norway.
The introduction of high-throughput sequencing (HTS) into clinical practice poses great challenges in terms of analytic resources, integration and data security. The project Norwegian clinical genetic Analysis Platform (genAP) was initiated as a response to these challenges, aiming to establish a centralised infrastructure for secure storage and analysis of human sequencing data that allows for disseminated clinical use. GenAP is a collaborative project between Oslo University Hospital and the University of Oslo, with implementation of the system in an established high-performance computing environment. As part of this project, we are in the process of establishing pilot HTS pipelines for a set of clinical packages, each with a defined set of targeted genes. The pilots cover diagnostic, prognostic and pharmacogenetic areas, including cardiomyopathies, breast cancer and tacrolimus dosage, respectively. Initially, the pipelines involve targeted capture and resequencing, but the system will be scalable to exome and genome data for a large number of patients. To reduce the workload associated with manual analysis, we have sought to achieve a high degree of automation, including variant annotation and quality control, filtering based on public resources, identification of previously classified variants, and standardization of report information structure for integration with existing patient journal systems. The pilot phase includes comparing the performance of HTS to conventional methods, building a database of genetic variants adapted to our patient populations and real-world testing using collaborating clinicians. The experiences gained will be used to expand to other clinical packages, and the ultimate goal is to introduce the pipelines for widespread use in the clinic. Complementing the genetic, bioinformatic and clinical issues, the project also addresses legal, ethical and organizational issues encountered when HTS is deployed in large scale clinical decision making.
This presentation will demonstrate the overall architecture of our system and present initial experiences with the pilot systems.
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