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

Emilia Zawadzka-Gosk; Krzysztof Wołk

doi:10.7494/csci.2018.19.2.2319

Authors

Emilia Zawadzka-Gosk Polish-Japanese Academy of Information Technology
Krzysztof Wołk Polish-Japanese Academy of Information Technology

DOI:

https://doi.org/10.7494/csci.2018.19.2.2319

Abstract

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

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