Evidence is mounting that genome sequencing should be performed as a first-tier test for children suspected of suffering from a genetic disorder in multiple pediatric settings, especially for those in the intensive care unit. As more children are sequenced, the pressures to increase the diagnostic rate and the time to result, while reducing the cost of the process, are amplified.
Interpretation of whole-genome or exome variants to diagnose rare genetic diseases continues to be a major bottleneck, as it often consists of time-consuming iterative variant filtering coupled with evidence review for large lists of candidate variants.
In this webinar, Dr. De La Vega will introduce the Fabric GEM AI algorithm and demonstrate how it significantly simplifies and improves disease-causing variant identification over prior methods, substantially reducing genome interpretation time in the diagnosis of monogenic disease, and could allow cost-effective, automated reanalysis of undiagnosed cases over time.Â
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