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In 2016, guidelines for diagnostic Next Generation Sequencing (NGS) have been published by EuroGentest in order to assist laboratories in the implementation and accreditation of NGS in a diagnostic setting. These guidelines mainly focused on Whole Exome Sequencing (WES) and targeted (gene panels) sequencing detecting small germline variants (Single Nucleotide Variants (SNVs) and insertions/deletions (indels)). Since then, Whole Genome Sequencing (WGS) has been increasingly introduced in the diagnosis of rare diseases as WGS allows the simultaneous detection of SNVs, Structural Variants (SVs) and other types of variants such as repeat expansions. The use of WGS in diagnostics warrants the re-evaluation and update of previously published guidelines. This work was jointly initiated by EuroGentest and the Horizon2020 project Solve-RD. Statements from the 2016 guidelines have been reviewed in the context of WGS and updated where necessary. The aim of these recommendations is primarily to list the points to consider for clinical (laboratory) geneticists, bioinformaticians, and (non-)geneticists, to provide technical advice, aid clinical decision-making and the reporting of the results.

Next-generation sequencing (NGS) technologies in clinical diagnostics open vast opportunities through the ability to sequence all genes simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand, the practical implementation of NGS in routine diagnostics involves a variety of challenges, which need to be overcome. Among these are the generation, analysis and storage of large amounts of data, strict control of sequencing performance, validation of results, interpretation of detected variants and reporting. Here, we outline the Multiple Integration and Data Annotation Study, an approach for data integration in clinical diagnostics based on genotype-phenotype correlations. MIDAS aims to accelerate NGS data analysis and to enhance the validity of the results by computer-based variant prioritization using the clinical data of the patient. In this context, we present the MIDAS case reports of one patient with intellectual disability caused by a novel de novo loss-of-function variant in the GATAD2Bgene [NM_020699.3: c.1426G>T (p.Glu476*)] identified by trio whole-exome sequencing, as well as two cardiac disease patients with severe phenotype and multiple variants in genes linked to cardiac arrhythmogenic disorders analyzed with multi-gene panel sequencing. Based on the data collected in the MIDAS cohort, the MIDAS software will be tested and optimized. Moreover, the MIDAS software concept can be extended modularly to include further data resources for improved data handling and interpretation in the broad field of diagnostics.