NOV 14, 2018 12:00 PM PST

Automated Variant Classification in QIAGEN Clinical Insight Shows Near Perfect Concordance with ClinVar Expert Panel Assessments

SPONSORED BY: QIAGEN
C.E. CREDITS: P.A.C.E. CE | Florida CE
Speakers
  • Principal Genome Scientist, Bioinformatics - Genetic Disease , QIAGEN
    Biography
      Jennifer received a B.S. in Genetics from the University of Connecticut and went on to receive a Ph.D. in Human Genetics at the Johns Hopkins School of Medicine. During her graduate training, she used Ingenuity Pathway Analysis and was so impressed with the tool that she approached QIAGEN for the opportunity to support their bioinformatics portfolio. Currently, she is the lead genome scientist supporting QIAGEN's software solutions for analysis and interpretation of variants implicated in hereditary disease.

    Abstract:

    As the compendium of putatively disease causing variants expands, gathering the most current and accurate information is critical to computing variant classifications. The QIAGEN knowledgebase includes the most extensively curated database of variant specific publications, including functional studies and clinical cases. QIAGEN Clinical Insight (QCI) leverages this information to invoke all ACMG rules to automatically compute variant classifications. In this webinar, you will see how QCI classifies over 6,000 ClinVar expert panel assessed BRCA1 and BRCA2 variants with incredible accuracy. With respect to clinical actionability, QCI automated ACMG classification was 99.6% concordant with ENIGMA expert panel variant assessments. This level of accuracy speaks to the quality of the clinical, functional, and population level data in the knowledgebase, as well as the robustness of the underlying algorithm used to apply the ACMG guidelines.


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