For lakes, the G&R interaction explained 10.6% of the variance in lake chemistry.
The G&L interaction explained 0.8% of the variance in stream and 2.1% of the variance in lake chemistry.
A common measurement of the interaction is the variance in the slope of the sire reaction norms, i.e. sire breeding values regressed on an environmental variable.
For some interaction models, the proportion of the variance that is epistatic rather than additive is greatest for interacting alleles at intermediate frequencies (Hill et al. 2008; Mackay 2014).
These interaction terms explained ≤ 0.01 of the variance in all species, except that the density*square interaction accounted for 0.07 of the variance in the vole.
Network size and topology, the width of the fitness function, pre-change additive variance, and certain interactions account for ∼75% of the variance in population recovery times after a sudden environmental change.
We finally reached a model containing VKORC1, CYP2C9*2 and *3, PROC, EPHX1, GGCX, ORM1-2, age, bodyweight and drug interactions which explained 73% of the variance in warfarin dose (Table 4).
This was because including interactions increases the variance of the liability score and, therefore, changes in threshold values are needed to accommodate the observed probabilities of each of the categories.
For all simulations, background variance was modeled such that, after accounting for the QTL-effect, the environmental main effect, and the interaction, 30% of the remaining variance was attributable to additive polygenic genetic effects (A), and 70% was due to non-shared environmental effects (E).
The L*S interaction accounts for only 1% of the variance.
