Virtual session discussing Fabric Genomics’ integrated analysis of structural variants and single nucleotide variants to improve diagnostic yields for whole genome sequencing in rare genetic diseases. The session is presented as part of the ACMG Annual Meeting.
Available as a prerecorded presentation beginning April 13, 2021.
Analysis of structural variants (SVs) along with smaller single nucleotide variants (SNVs) can improve diagnostic yield of whole genome sequencing in rare disease cases by as much as 15 percent, but analyzing SVs is fraught with challenge. In a study involving 56 rare genetic disease cases with causal SVs, Fabric GEM – Fabric Genomics’ AI gene-ranking algorithm – provided a unified approach to analyzing SVs and SNVs in a single step, correctly identifying 96 percent of these SVs. Moreover, GEM identified the causal SV in the top five list of all candidates (SVs and SNVs) 93 percent of the time, requiring review of fewer than five candidates per case. These results hold promise for patients seeking answers to undiagnosed diseases.
The study was conducted in conjunction with Rady Children’s Institute for Genomic Medicine, the University of Utah, and the Utah Center for Genetic Discovery.
Fabric GEM is currently optimized for analyzing SVs from whole genome data, giving physicians the most comprehensive genetic test possible.
To access the 30-minute ACMG Product Theater presentation, log on beginning April 13th at 9 a.m. EDT via this media advisory.
Fabric Genomics is making genomics-driven precision medicine a reality. The company provides clinical-decision support software that enables clinical labs, hospital systems, and country-sequencing programs to gain actionable genomic insights, order-of-magnitude improved diagnostic yields and turnaround time. Fabric’s end-to-end genomic analysis platform incorporates proven AI algorithms and has applications in both hereditary disease and oncology. Headquartered in Oakland, California, Fabric Genomics was founded by industry veterans and innovators with a deep understanding of bioinformatics, large-scale genomics, and clinical diagnostics.
To learn more, visit fabricgenomics.com and follow us on Twitter and LinkedIn.
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