From Genome Analysis Wiki
Jump to navigationJump to search
16 bytes added
, 10:46, 11 March 2014
Line 9: |
Line 9: |
| <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 <math>\mathbf{0}</math> 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 <math>\mathbf{I}</math> is the identity matrix. | + | We assume that genetic effects are normally distributed, with mean <math>\mathbf{0}</math> 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 <math>\mathbf{0}</math> and covariance <math>\mathbf{I}\sigma_e^2</math>, where <math>\mathbf{I}</math> is the identity matrix. |
| | | |
| == Single Variant Score Tests == | | == Single Variant Score Tests == |