NOV 02, 2016 06:00 AM PDT

Fast and easy identification of disease causing variants in hereditary diseases using patient phenotype information and testing for different modes of inheritance

C.E. CREDITS: P.A.C.E. CE | Florida CE
  • Director, Global Product Management, Clinical Program; QIAGEN Bioinformatics
      Anika Joecker is a director in the global product management department in the clinical program of QIAGEN bioinformatics. She has been working in the field of bioinformatics for the last 15 years and worked as a bioinformatics group leader at the German Cancer Research Center before she joined CLC bio, now QIAGEN in 2011.


    Whole genome and exome sequencing is being widely used to identify disease-causing variants in patients with hereditary and rare diseases. Discovering the true disease-causing variants often requires testing different modes of inheritance (de novo, compound heterozygote, recessive, or dominant). Indeed, selecting the most promising ones that best explain a patient’s entire phenotype, can be very time-consuming. In this presentation, we will present our new one-step trio workflow, which automatically checks for all modes of inheritance using optimized parameter settings for the complete data analysis, filtering, and interpretation workflow. We will illustrate this by reporting data from cases with undiagnosed genetic disorders. In combination with our new patient phenotype-driven sorting algorithm, which ranks variants using phenotype-disease associations, this simplifies and accelerates the identification of disease-causing variants. 

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