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beta from linear regression, odds ratio from logistic regression or best linear unbiased prediction (BLUP) from linear-mixed models (Yang et al. Secondly, for each individual within the target sample a GRPS is computed by taking the number of risk alleles an individual possesses weighted by the effect size of that allele from the discovery sample, averaged over the number of loci included in the GRPS.
The GRPS and the environmental variable of interest can now be included as individual terms as well as a product term in a risk-profiling framework. Fitting nested (increasingly more restricted) models allows testing for significance of the GRPS, the environmental factor of interest, and their interaction effect.
For a disease trait (binary Y ), the full logistic regression equation will be.