Sentence examples for trait divided by from inspiring English sources

The mean of each trait divided by genotype is presented as the recessive and dominant models.

Mean number of eggs and mean calling effort were calculated for individuals as the sum of the values of the respective trait, divided by the number of measures at which the animal was alive.

Genetic correlations across environments were calculated as the covariance between traits divided by the square root of the product of both trait variances.

Furthermore, the final heritability for the trait was divided by a factor 2.5 at generation 500.

Genetic selection gradients were obtained by bivariate analysis (to reduce the bias in the estimation, see [ 9, 12]), as the genetic covariance between the trait and fitness divided by the genetic variance of the trait, for the traits estimated in the two experiments.

To obtain the standardized genetic selection gradients, the genetic covariance between standardized trait and fitness was divided by the additive genetic variance of the trait.

This was specifically calculated as the mean trait value of the introduced lineage minus the mean trait value of the native lineage, divided by the mean trait value of the native lineage, and multiplied by 100.

Therefore, the prior distribution for V in this case was, according to Meuwissen and Goddard [ 11]: where S 0 (no ) was chosen such that it reflected the total genetic (co variance between traits n and o, divided by the total number of SNP.

According to Meuwissen and Goddard (2004), in this case the prior distribution of V.. is similar to that from model 3, but here S 0 was chosen such that it reflected the total genetic (co variances of traits n and o, divided by the total number of expected QTL instead of the number of SNP.

We therefore also computed the rph-a, rph-c and rph-e: rph-a can be seen as the correlation that would have been observed if only genetic factors play a role and is defined as the covariance between two trait due to genetic factors, divided by the sqrt of variances of those two traits.

In the case of a single trait, the genetic selection gradient (βA) is defined as the genetic covariance between the trait and relative fitness (σa,w) divided by the additive genetic variance in the trait (σa) [ 27]: (Eq.1) β A = σ a, ω σ a 2 The selection analysis can be easily extended to the multivariate case, to account for selection on correlated characters [ 28].