Facilitating NGS-Based Screening of Genetic Disorders Using -AI-Driven Bioinformatics

Abstract

Next-Generation Sequencing (NGS) is used as a diagnostic strategy for identifying pathogenic genetic variants in children and adults. However, the analysis is complex, requiring specialized bioinformaticians, and it can take weeks to finalize one study. This has been a limiting factor for the application of NGS in the screening of populations for rare genetic diseases. In this work, we show two case studies, where we applied an AI-driven bioinformatics framework in a diagnostic and a preventive scenario, respectively. The AI analysis was accurate and substantially faster than using conventional bioinformatics tools. Our results support the concept that AI-driven bioinformatics is a scalable solution for rendering accurate results and enabling a more widely available genetic screening for rare diseases.

Keywords

• genomics
• bioinformatics
• rare diseases
• artificial intelligence
• pre-conception