Sentence examples for main effect explained from inspiring English sources

On the other hand, the pairs of environments showing correlations larger than 0.3 (2iBN + 5iBNZ and 2iBN + 5iFN) gave estimates of variance components where the main effect explained between 50 and 70% of the genomic variance.

Finally, in W1, the pair of environments with the largest sample phenotypic correlation (0iBN + 2iBN) had estimates of variance components such that the main effect explained about 80% of the total genomic variance.

For Design(−i,a) and Design(−i,a,e) on the other hand, the QTL main effect explained 0% of the variance as the actual effect of the QTL was nullified entirely by the reversed interaction effect.

Indeed, in W2, the main effects of markers explained more than 60% of the genomic variance for pairs of environments having sample phenotypic correlations greater than 0.33 (Table 4); on the other hand, in the two environments showing a low correlation (0iFN + 5iBN), the main effect explained only about 10% of the genomic variance.

For instance, in W1, the analysis of pairs of environments exhibiting sample phenotypic correlations smaller than 0.3 (0iBN + 5iBNZ, 0iBN + 5iFN, and 5iBNZ + 5iFN) yielded estimates of variance components in the M×E model where the main effect explained less than 50% of the total genomic variance, computed as the sum of the main effect plus interaction variance estimates (see Table 3).

A scenario such as this where main effects explain little of the overall outcome variance represents a very difficult problem [ 53] for an evolutionary search procedure to model.

The main effect QTL explained from 1 to 14% of the phenotypic variance.

The factor iTarget was the main effect and explained 42.4% of the data variability.

The risk variants at these pairs had low main effects but explained a relatively high-level variance of the amyloid deposition in cingulate (Table 2).

In the case of heavy metals, biosorption studied in this work, the speciation of the metals is not changed with the pH (constant in the process), therefore, the main effect will be explained by the impact of this parameter on the functional groups of the biomass.

On the other hand, the strong correlation between STP and both decay time and half width suggests that details of the decay phase may be less relevant and that the main effect can be explained by the time span the membrane potential spends close to spike threshold.