A Scalable Approach to Resolving Variants of Uncertain Significance

Description

Experimental functional data and computational predictions are the only two scalable sources of evidence for variant classification. However, use of experimental and predictive data in the clinic has been limited; experimental data is lacking for most genes, both data sources are difficult to translate into clinical evidence, and there is limited dissemination infrastructure. The NHGRI's Impact of Genomic Variation on Function consortium overcame these barriers by building production-scale multiplexed experimental platforms, developing improved calibration methods for experimental and predictive data and creating interactive web resources to deliver this calibrated evidence to clinicians. 

 

Level of Instruction
Intermediate - Refresher course; some basic knowledge of subject recommended
 

Learning Objectives

1. Review sources of evidence for variant classification and their benefits and drawbacks.
2. Identify the difference between functional and computation data and functional and computational evidence.
3. Identify and use resources for functional and computational evidence.

Course summary

Available credit: 
  • 0.10 NSGC CEU
Course opens: 
04/02/2026
Course expires: 
04/02/2028
Cost:
$0.00

Presenter: Lea Starita, PhD

Co-director of the Advanced Technology Lab, Brotman Baty Institute for Precision Medicine

Lea is an Assistant Professor of Genome Sciences at the University of Washington and co-director of the Advanced Technology Lab at the Brotman Baty Institute for Precision Medicine. My goal is to eliminate VUS and to make genomic information more informative, equitable and impactful by delivering high quality functional data that have been systematically analyzed and packaged for rapid uptake to clinicians and industry. To achieve that goal, my research program has three main directions: 1) developing new multiplexed assays for variant effect (MAVE) technology to access to new and more informative phenotypes, 2) scaling existing MAVEs for broad application, and 3) breaking down barriers to the systematic application of functional data to clinical variant interpretation workflows. 

 

 

Moderator: Katherine Crawford, MS, CGC

Clinical Science Liaison at Ambry Genetics

Katie is a Clinical Science Liaison at Ambry Genetics working with oncology, rare disease, and exome. She has previously worked clinically at Women & Infant's Hospital of Rhode Island for over five years as an oncology genetic counselor. She is a graduate of the Arcadia University Genetic Counseling Program and has numerous scientific publications in the fields of oncology, neurology, epidemiology, and psychiatry.

 

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Ambry Genetics is approved as a provider for continuing education program by NSGC and ASCLS P.A.C.E ® Programs.

Credit eligibility varies by activity; please see below for the specific credit types offered for this course.

Available Credit

  • 0.10 NSGC CEU

Price

Cost:
$0.00
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