Sentence examples for marker effect estimation from inspiring English sources

In this paper, the weights were derived from the marker effect estimation step which increases the computational burden.

However, the marker effect estimation step might be not necessary as marker weights could be provided by existing genome-wide association studies (GWAS) or known candidate-gene effects.

Phenotypes in the training set were used for marker effect estimation.

For marker effect estimation, the mean of r plot values per DH line was calculated.

With both approaches, marker effect estimation took less than a second for all investigated data sets.

Rather, this source of LD just generates noise, reducing marker effect estimation accuracy Increasing the heritability of measurements increases the accuracy derived from this source of LD when predictions are applied within the training population.

In the step estimating marker effects, the estimation of effects of very many markers is hampered by the LD, i.e. collinearity, between the marker effects.

This approach gave early benefits but in later generations, without updating marker effects, the estimation of marker effects based on less related reference individuals did not pay off.

This introduces the important issue of the persistence of GWEBV predictions over generations in the absence of marker effects re-estimation, and few studies have examined this issue, e.g. [ 11].

In the estimation of the marker effect, the penalty parameter λ is chosen to have a value of: 1 − h 2 h 2 V a r (X ), where h is the narrow sense heritability and Var(X) is the sum of the 2000 marker variances.

Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS).