About this webinar

Recorded On: Wednesday, May 2, 2018

To fully interpret variants in the context of clinical genomics, as outlined by the ACMG interpretation guidelines, variants near canonical splice boundaries must be evaluated for their potential to disrupt gene splicing and thus be classified as a gene-damaging mutation. Five splicing methods have been canonized for this purpose in the clinical testing market: GeneSplicer, MaxEntScan, NNSplice, and Position Weight Matrix (PWM). Although these algorithms vary wildly in their performance characteristics, such as sensitivity and specificity, they are treated as black-box oracles on equal footing when being used by variant curators to classify variants.

In this presentation, we will review these algorithms and their technical strengths and weakness from the perspective of clinical variant interpretation. Additionally, we will present our approach to splice site prediction within VarSeq, demonstrating how we improve on the status quo by employing these algorithms both in the batch annotation and genomic visualization contexts. Finally, we will demonstrate how these methods can be leveraged during the interpretation of variants following the ACMG guidelines within our upcoming product, VSClinical.