dominance: Report dominance parameters
In jendelman/StageWise: Two-stage analysis of multi-environment trials for genomic selection and GWAS
dominance R Documentation
Report dominance parameters
Description
Report dominance parameters
Usage
dominance(params, index.coeff = NULL, gamma = 0)
Arguments
params
list returned by Stage2
index.coeff
merit index coefficients
gamma
contribution of non-additive values for genetic merit
Details
The dominance variance (Vd) and baseline heterosis (b) are quantified relative to additive variance (Va) and std. dev. (SDa), respectively. As of v1.11, the variances are scaled to the population (previously, it was just the variance components). For a multi-trait/loc model, index.coeff specifies the coefficients of the standardized true values (see also blup), with gamma indicating the relative weight of non-additive to additive genetic merit for the standardization (see also gain).
Value
data frame with estimates and SE
jendelman/StageWise documentation built on Feb. 23, 2025, 11 a.m.
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| dominance | R Documentation |
Report dominance parameters
Description
Report dominance parameters
Usage
dominance(params, index.coeff = NULL, gamma = 0)
Arguments
params |
list returned by |
index.coeff |
merit index coefficients |
gamma |
contribution of non-additive values for genetic merit |
Details
The dominance variance (Vd) and baseline heterosis (b) are quantified relative to additive variance (Va) and std. dev. (SDa), respectively. As of v1.11, the variances are scaled to the population (previously, it was just the variance components). For a multi-trait/loc model, index.coeff specifies the coefficients of the standardized true values (see also blup), with gamma indicating the relative weight of non-additive to additive genetic merit for the standardization (see also gain).
Value
data frame with estimates and SE
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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