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

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.

Jessica Vionas

About Jessica Vionas

Jessica Vionas is the Director of Marketing at Golden Helix and as such, she is responsible for creating a comprehensive marketing, communications, and public relations strategy to position the company in the life sciences marketplace and ensure a consistently full sales funnel to meet and exceed revenue goals. Prior to joining Golden Helix in May of 2010, Jessica worked for eight years in the marketing department at a credit evaluation software company based in Bozeman. She received her Bachelor of Science in Sociology from Montana State University in 2006. When not at the office, Jessica enjoys playing with her dog Athena, reading marketing books, and spending time with her friends and family, preferably in the bright sunshine of Montana.
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One Response to Upcoming webcast – Mixed Models: How to Effectively Account for Inbreeding and Population Structure in GWAS

  1. Jessica Vionas says:

    You can access the recording of this webcast at: http://www.goldenhelix.com/Events/recordings/mlm/index.html

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