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.

Mary Makris

About Mary Makris

Mary Makris joined Golden Helix in March 2015 and is the Marketing & Operations Manager. Mary graduated from the University of Montana in May 2014 with a bachelor's degree in Marketing and a minor in Psychology. She is responsible for executing marketing strategies, maintaining the company's social media and web presence, and assisting in all other areas of the marketing department. In her free time, she enjoys playing soccer, biking, fishing, and being crafty.

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