About this webinar
Recorded On: Wednesday, June 6, 2018
Clinical Genetic testing requires a complex analysis using the totality of our knowledge about the clinical relevance of a variant and a gene. This includes bioinformatic evidence as well as clinical evidence. The ACMG Guidelines provided a framework in which to score variants based on this evidence, and while some of those scoring criteria require close consultation of the clinical context for a given patient, much of it can be automated.
In this webcast, we review how VSClinical automates the ACMG scoring guidelines while integrating the collective lab expertise from previously classified variants and preferences about genes. We will cover:
- Using the ACMG Auto Classifier as part the filtering strategy for gene panels and trio workflows
- How gene preferences such as the default transcript, inheritance model, and disorder are updated and saved from VSClinical and used in all future analysis
- How the per-variant recommendation engine builds on the auto-classification with descriptive reasons for answering each criterion yes or no
- Using the auto-interpretation to present the evidence for all scored criteria in a human-readable paragraph
- Working with VSClinical’s self-learning knowledgebase that incorporates previously classified variants and genes inform the interpretation of new variants!
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