For many labs, scaling the analysis of genome sequence data for rare genetic disease cases presents a challenge. Traditional filtering approaches can leave analysts with hundreds of variants to interpret, increasing the turn-around time and leading to reviewer fatigue.
In this webinar, Jaime Lopes, laboratory director at Cincinnati Children’s Hospital, will present the hospital’s transition to a streamlined variant interpretation workflow that utilizes Fabric Genomics’ software and AI-driven gene prioritization algorithms. Lopes will present data that demonstrates how an AI-guided approach can reduce the number of variants to interpret, allowing variant scientists to focus more attention on a smaller number of high-quality candidates and, in turn, produce clinical grade results in a fraction of the time. Following Lopes’ presentation, Jeanette McCarthy will discuss how labs can extend their analysis to include prioritization and interpretation of copy number variants using Fabric’s software and AI.