Semantic-Enabled Hybrid Genetic Disease Diagnostics in Next-Generation Sequenced Data

Abstract

Next Generation Sequencing is a technology for genome sequencing used in genetics for the diagnosis of disease. NGS provides a list of all mutations in a genome, so identifying the one that causes a disease is not trivial. A number of applications for variant prioritization were developed, but the data they provide is a suggestion rather than a diagnosis; moreover, they suffer from issues such as identifying a nonpathogenic variant as a causal one or the inability to identify a causal gene. These issues inspired us to create a strategy for variant prioritization, which includes the use of the Exomiser and OMIM Explorer result sets improved by semantic analysis of abstracts and articles freely available from the PubMed and PubMed Central databases. For the wider scope of scientific articles, the Google Scholar repository will be used. The described approach enables us to present the latest and most accurate information about potential pathogenic variants.