When applying genomic methods to identify causal variants for patients with undiagnosed rare or not so rare disease, the primary goal is to report one or more deleterious variants that result in the patients clinical presentation. Typically, this is done through identification and then filtering and prioritization of variants with follow up expert review for reporting. Variant impact ascertainment and prioritization remains a challenging task due to the complexity of biological networks, the high degree of both phenotypic and molecular variability, and the volume of reference data to be considered. Application of methods that can prioritize variants in the presence of such complexity are clearly of critical importance to minimize the manual steps and thus time taken for interpretation. I will discuss the methods we have developed to identify and prioritize such variation. We can correctly classify the vast majority of variants previously human interpreted as pathogenic into the “should be clinically reported” category without human intervention and are now integrating these into the tools we use for molecular diagnostics at UAB.
Application of Novel Methods and Algorithms for Identification and Prioritization of Deleterious Variants
Associate Professor, Division of Pediatric Hematology and Oncology
Director, Center for Genomic Data Sciences
The University of Alabama at Birmingham
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