Genome-wide association study (GWAS) technology has been a primary method for identifying the genes responsible for diseases and other traits for the past ten years. GWAS continues to be highly relevant as a scientific method. Over 2000 human GWAS reports now appear in scientific journals. In fact, we see its adoption increasing beyond the human-centric research into the world of plants and animals. GWAS studies have been beneficial in agrigenomics for identifying genes associated with milk production in the dairy industry, coat color in sheep, along with identifying disease resistance in plants. Identifying the genes of interest for these traits allows farmers to selectively breed for the more desirable trait.
This eBook aims to explain the basic steps and concepts to complete a GWAS experiment and address how these steps are implemented in SVS. In Chapter 1, we start with an introduction to GWAS exploring its biology and origins, as well as the practical use of GWAS. Next, we will look at performing a GWAS in the context of the SVS software, discussing quality control, including sample statistics, heterozygosity, LD pruning, population stratification and identity by descent. We also take a look at how to impute data within SVS. From there we move on to genotype association testing, and we close with a walk through conducting a Meta-Analysis in SVS.
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