Genomic Breeding Tools: Genetic Variance Prediction and Cross-Validation


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Documentation for package ‘PopVar’ version 1.3.1

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PopVar-package Genomic breeding tools to 1) predict standard statistics and correlated response in plant populations, and 2) performs cross-validation to estimate genome-wide prediction accuracy
calc_marker_effects Internal functions
cross.tab_ex An example barley dataset
G.in_ex An example barley dataset
G.in_ex_imputed An example barley dataset
G.in_ex_mat An example barley dataset
internal Internal functions
maf_filt Internal functions
map.in_ex An example barley dataset
mppop.predict Predict genetic variance and genetic correlations in multi-parent populations using a deterministic equation.
mppop_predict2 Predict genetic variance and genetic correlations in multi-parent populations using a deterministic equation.
par_name Internal functions
par_position Internal functions
pop.predict A genome-wide procedure for predicting genetic variance and correlated response in bi-parental breeding populations
pop.predict2 Predict genetic variance and genetic correlations in bi-parental populations using a deterministic model
PopVar Genomic breeding tools to 1) predict standard statistics and correlated response in plant populations, and 2) performs cross-validation to estimate genome-wide prediction accuracy
pop_predict2 Predict genetic variance and genetic correlations in bi-parental populations using a deterministic model
tails Internal functions
think_barley.rda An example barley dataset
x.val Estimate genome-wide prediction accuracy using cross-validation
XValidate_Ind Internal functions
XValidate_nonInd Internal functions
y.in_ex An example barley dataset