New Enhancements:

GWAS Workflows with SVS

About this webinar

Recorded On: Wednesday, August 9, 2017

In this webcast we focus on the recent improvements to our research product SNP & Variation Suite. Over the past 12 months, we have continued to expand on the tools SVS provides to the researcher doing association studies, whether from standard GWAS workflows or complex custom Large-N studies.

Based on user requests, we have added features from a couple of recent papers and their corresponding method packages to compute heritability estimates, understand the genetic correlation between two traits and improve our GBLUP methods to correct for gene by environmental factors.

In this webcast, we review these new additions and how they fit into the existing SVS research platform. We will cover:

  • How to differentiate inflated correlation from population structure using LD Regression Score heritability estimates
  • Alternative options for computing the genomic relationship matrix (GRM) including the option to correct for gene by environment interactions
  • Compare the genetic component of two traits using both heritability scores and bivariate GBLUP analysis

SVS continues to move forward based on the ongoing feedback of the user community, and in this webcast we share the highlights of these recent user-driven features and how they improve the SVS workflows for advanced genotype analysis.

Watch on demand

Please enjoy this webcast recording. Should you have any questions about the content covered, please reach out to our team here.

Download the slide deck

To download a copy of the slides, click on the LinkedIn icon. This will redirect you to the SlideShare site. From there, you can clip your favorite slides or download the entire deck to your computer.

Love this webcast? Check out more!

Find out how Golden Helix software enables users to harness the full potential of genomics to identify the cause of disease, improve the efficacy and safety of drugs, develop genomic diagnostics, and advance the quest for personalized medicine.