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A Quick Guide to the Analytics Behind Genomic Testing

 

This course features introductory information about the role of bioinformatics in clinical genomic testing by NGS from the perspective of a national reference laboratory. An overview of the various types of bioinformatics pipelines, variant detection methods, and the computational infrastructure supporting these analytical pipelines will be discussed. This course will end with an overview of the validation strategy for bringing a new bioinformatics platform online for clinical production.

Originally presented on December 28, 2017, in Salt Lake City, Utah.

Lecture Presenter

Elaine Gee, PhD

Elaine Gee, PhD

Director of Bioinformatics
ARUP Laboratories

Dr. Gee is the director of Bioinformatics at ARUP. She leads teams of bioinformaticians, software programmers, data engineers, and analysts to generate analytical pipelines for processing raw NGS data for germline and somatic variant calling, as well as applications in infectious disease. Her team has scaled best-practices pipelines, built compute infrastructure in the cloud, and created a robust genomic data warehouse. Her background extends beyond genomics testing and includes cross-disciplinary work in signal processing, molecular dynamics modeling, and instrument integration and control. Dr. Gee received her PhD in biophysics from Harvard University and a bachelor of science in physics from the California Institute of Technology.

Objectives

After this presentation, participants will be able to:

  • Catalogue various types of bioinformatics analyses that support clinical genomic testing
  • Enumerate types of variant classes
  • Describe algorithmic methods for variant detection by NGS
  • Compare and contrast germline and somatic clinical bioinformatics pipeline methodologies
  • Discuss the infrastructure complexity required to support analytics for NGS testing at scale in the cloud
  • Introduce validation strategies for bringing best-in-class pipelines into clinical production

Sponsored by:

University of Utah School of Medicine, Department of Pathology, and ARUP Laboratories