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<math>\mathbf{y}=\mathbf{X}\beta +\mathbf{g}+ \boldsymbol{\varepsilon}</math>
<math>\mathbf{y}=\mathbf{X}\beta +\mathbf{g}+ \boldsymbol{\varepsilon}</math>
We assume that genetic effects are normally distributed, with mean '''0''' and covariance <math>\mathbf{K}\sigma_g^2</math> where the matrix '''K''' summarizes kinship coefficients between sampled individuals and <math>\sigma_g^2</math> is a positive scalar describing the genetic contribution to the overall variance. We assume that non-shared environmental effects are normally distributed with mean '''0''' and covariance <math>\mathbf{I}\sigma_e^2</math>, where I is the identity matrix.
== Single Variant Score Tests ==
== Single Variant Score Tests ==
