Calling Large LOH and CNV Events with NGS Exomes
Next Generation Sequencing Exomes are a powerful assay used in both clinical and research settings to discover novel and rare small variants. Now a mature part of many labs, exomes consistently provide coverage over hundreds of thousands of targets across the genome.
Along with the small variants, exomes can also be used to call Copy Number Variations, providing extra value for data you may already have and discovering events that may not be captured by any of your existing testing technology.
In this webinar, we will address common questions about calling large events on exome data, including:
- To what extent can Exomes replace Chromosomal MicroArrays (CMAs) for calling large Copy Number Variations (CNVs)
- What is the validation strategy for a CNV calling method that finds everything from single-exon events to whole chromosome aneuploidy?
- How Loss of Homozygosity and Copy Number calls be integrated into one analysis and interpretation workflow
Watch as we review the next generation CNV and LOH calling algorithm coming to VarSeq and provide case-studies and examples of the capabilities of this algorithm and how it fits into the existing powerful VarSeq platform
About the Presenters
Gabe Rudy is GHI's Vice President of Product Development and team member since 2002. Gabe thrives in the dynamic and fast-changing field of bioinformatics and genetic analysis. Leading a killer team of Computer Scientists and Statisticians in building powerful products and providing world-class support, Gabe puts his passion into enabling Golden Helix's customers to accelerate their research. When not reading or blogging, Gabe enjoys the outdoor Montana lifestyle. But most importantly, Gabe truly loves spending time with his sons and wife. Follow Gabe on Twitter @gabeinformatics.
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.