NOV 02, 2016 6:00 AM PDT

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

Speaker
  • Associate Director Global Product Management NGS, QIAGEN
    Biography
      Dr. Anika Joecker is Associate Director Global Product Management NGS at QIAGEN. She joined CLC bio (now QIAGEN) in 2011 as Senior Bioinformatician/Project & Team Manager and worked since 2013 in product management at QIAGEN - first in Bioinformatics and recently now as product manager of the GeneReader NGS System. Anika Joecker holds a Ph.D. in Biology/Bioinformatics from University of Cologne, Germany, and has worked as Bioinformatics Group Leader at the German Cancer Research Center (Heidelberg, Germany).

    Abstract

    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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