CNV Analysis in VarSeq
Numerous studies have documented the role of Copy Number Variations (CNVs) in human health with associated phenotypes including cancer, obesity, cognitive disability and numerous other maladies. Yet currently, detection of CNVs on targeted gene panels requires an alternative assay such as Chromosomal Microarrays (CMAs). As a result, current CNV detection techniques are expensive, slow and are only capable of detecting large multi-exon events.
In this webcast, we will demonstrate a new VarSeq algorithm for calling CNVs from NGS coverage data. This will include a discussion of:
- Challenges involved in CNV detection
- Metrics used to call CNVs from NGS data
- Need for representative reference samples
- Requirements for using this tool on your existing data
- Process for calling of CNVs in VarSeq
- Validation and reporting of CNV events
About the Presenter
Nathan Fortier joined the Golden Helix development team in June of 2014 and is a Senior Software Engineer and Field Application Scientist. Nathan obtained his Bachelor’s degree in Software Engineering from Montana Tech University in May 2011 and received a Master’s degree as well as a PhD in Computer Science from Montana State University. Nathan works on data curation, script development, and product code. When not working, Nathan enjoys hiking and playing music.