Using VS-CNV to detect high-quality CNV events

Abstract

Copy number variations (CNVs) are characterized by a deletion or duplication of segments of the genome and can alter many properties of genes and their functionality. As such, CNVs are known to contribute to a considerable number of Mendelian disorders including developmental delays, spinal muscular atrophy, autism, Alzheimer disease, and schizophrenia. With the increasing knowledge of the impact of CNVs on the human genome, it is essential to have software that can identify these structural variations. VS-CNV is well equipped to detect not only events but also utilize the same filtering and annotation capabilities used with SNVs/indels/deletions. The focus of this presentation will be to demonstrate how to screen-detected events utilizing supporting metrics, quality criteria, and previous findings to eliminate potential false positive events.

About the Presenter

Eli Sward, Ph.D

Eli Sward, Ph.D, is a Field Application Scientist at Golden Helix, joining the team in May of 2018. Eli graduated from Montana State University with a bachelor’s degree in Microbiology, and a doctorate’s in the Department of Immunology and Infectious Diseases. Beyond providing customer support and training at Golden Helix, Eli enjoys many outdoor activities and spending quality time with family and friends.