The implementation of next-generation sequencing (NGS) in a clinical diagnostic setting opens vast opportunities through the ability to sequence all genes contributing to a certain morbidity simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand, the practical implementation of NGS in a clinical diagnostic setting involves a variety of new challenges, which need to be overcome. Among these are the generation, analysis and storage of unprecedented amounts of data, strict control of sequencing performance, validation of results, interpretation of detected variants and reporting. In the following sections, key aspects of data management and integration will be discussed. In particular, issues of data storage, data analysis using in-house IT infrastructure vs. data analysis employing cloud computing and the need for data integration from different sources will be covered.
CITATION STYLE
Eck, S. H. (2018, December 1). Challenges in data storage and data management in a clinical diagnostic setting. Journal of Laboratory Medicine. Walter de Gruyter GmbH. https://doi.org/10.1515/labmed-2018-0054
Mendeley helps you to discover research relevant for your work.