These MME*.R scripts had two aims. First to to provide an independent validation of results presented in the paper, 
and second to demonstrate that methods 1, 2 and 3 for the complete omics case are equivalent. The implementation is not computationally efficient, 
and requires large amounts of memory and also takes some time to run. See details in each of the scripts.

In these scripts, the omics expression is standardised such that omics for each feature has mean zero and variance 1/n.features. 
The implication is the omics similarity matrix has average of diagonal elements equal to 1, and sigma*2_g= h2m, sigma2e=1-h2m is be used for 
similarity matrices in the incomplete omics case. The ratio's needed in the MME are functions of c2m (microbiobility), h2m (heritability of omics)
and h2ar (residual heritability), and note the formula h2=c2m*h2m+h2ar from the paper. The ratios needed for the MME are
eta1 = var_epsilon/(c2m*var_y)= (1-c2m-h2ar)/c2m
eta2 = var_epsilon/var_ar = (1-c2m-h2ar)/h2ar
zeta = (1-h2m)/h2m

Input files (to be found at http://genoweb.toulouse.inra.fr/~alegarra/GOBLUP/) are
M.txt: omics expression levels
G: genomic relationship matrix
Gi: inverse of genomic relationship matrix
y: vector of phenotypes
tbv.txt: true genetic effects

Output files are 
EBV1, EBV2 and EBV3 (referring to methods 1 2 and 3 respectively) for the complete omics case.
EBVsmall (referring to method 2 on 4000 individuals), EBVss2 and EBVss3 (referring to extensions of method 2 and 3 respectively) for incomplete omics case.

The file results.R presents an investigation of results in terms of accuracy and dispersion bias. Here the file tbv.txt with true genetic effect is needed.