Upcoming webcast – Mixed Models: How to Effectively Account for Inbreeding and Population Structure in GWAS

Presenter: Greta Linse Peterson, Senior Statistician
Date: Wednesday, June 5th, 2013
Time: 12:00 pm EDT, 60 minutes

Abstract
Population structure and inbreeding can confound results from a standard genome-wide association test. Accounting for the random effect of relatedness can lead to lower false discovery rates and identify the causative markers without over-correcting and dampening the true signal.

This presentation will review four different methods of analyzing genotype data while accounting for random effects of relatedness. Methods include PCA analysis with Linear Regression, GBLUP, EMMAX, and MLMM. Comparisons will be made using data from the Sheep HapMap project and a simulated phenotype. After presenting the various methods, we will discuss how these results can be obtained using Golden Helix SNP & Variation Suite (SVS) software and how SVS can be used to compare and contrast the results.

Delaina Hawkins

About Delaina Hawkins

Delaina Hawkins is the Content Marketing Manager at Golden Helix, joining the team in June of 2017. She is passionate about the digital and social media landscape and elevating a company to effectively grow user engagement, build brand loyalty and ultimately drive sales and revenue. When she isn't in the office, she enjoys fishing, biking and spending time with family and friends.

One thought on “Upcoming webcast – Mixed Models: How to Effectively Account for Inbreeding and Population Structure in GWAS

Leave a Reply

Your email address will not be published. Required fields are marked *