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== A Simple Genetic Association Study ==

== A Simple Genetic Association Study ==

In this example, we will use [http://www.r-project.org/ R] to carry a simple power calculation for a genetic association study. We will assume that you are interested in a quantitative trait and that you have phenotyped and genptyped ''N'' randomly sampled individuals. Further, we will assume that you are using signficance level <math>alpha</math> for your analyses (typically, <math>alpha = 0.05 / M</math> where ''M'' the number of independent markers examined) and ''H2'' is the variance explained by additive effects at the marker of interest.

In this example, we will use [http://www.r-project.org/ R] to carry a simple power calculation for a genetic association study. We will assume that you are interested in a quantitative trait and that you have phenotyped and genptyped ''N'' randomly sampled individuals. Further, we will assume that you are using signficance level <math>alpha</math> for your analyses (typically, <math>alpha = 0.05 / M</math> where ''M'' the number of independent markers examined) and ''H2'' is the variance explained by additive effects at the marker of interest under an additive model.

 

Thus, we are assuming that you will ultimately analyze your data with a linear model such as <math>E(Y_i) = \mu + \beta_G * G_i</math>, with <math>E(Y_i)</math> denoting the expected phenotypic value for each individual, <math>\mu</math> denotine an overall mean, <math>\beta_G<\math> denoting the estimated per genotype effect, and <math>G_i<\math> denoting the observed genotype for each individual (coded as 0, 1 or 2 according to the number of copies of the rare alelele).

In this setting, a simple power calculation might look like:

In this setting, a simple power calculation might look like: