output.best: Summary For The Best Individuals

In IPLGP: Identification of Parental Lines via Genomic Prediction

Summary For The Best Individuals

Description

Output the GEBV average curves and the summary statistics for the best individuals selected over generations.

Usage

output.best(result, save.pdf = FALSE)

Arguments

result	list. The data list of the output from simu.GEBVO, simu.GDO, or simu.GEBVGD.
save.pdf	logical. A logical variable, if save.pdf is set to be TRUE, the pdf file of plots will be saved in the working directory instead of being shown in the console.

Value

The GEBV averages of the best individuals among the repetitions over generations for each trait.

Note

The figure output contains the plots of GEBV averages of the best individuals selected over generations for each trait. If save.pdf is set to be TRUE, the pdf file of plots will be saved in the working directory instead of being shown in the console.

References

Chung PY, Liao CT. 2020. Identification of superior parental lines for biparental crossing via genomic prediction. PLoS ONE 15(12):e0243159.

See Also

simu.GEBVO simu.GDO simu.GEBVGD ggplot

Examples

# generate simulated data
set.seed(2000)
t1 <- rnorm(10,30,10)
t2 <- rnorm(10,10,5)
t3 <- NULL
t4 <- NULL
t5 <- NULL
geno.test <- matrix(sample(c(1, -1), 200, replace = TRUE), 10, 20)
marker.test <- cbind(rep(1:2, each=10), rep(seq(0, 90, 10), 2))
fit <- GBLUP.fit(t1, t2, t3, t4, t5, geno = geno.test)
fitvalue <- fit$fitted.value

geno.candidate <- matrix(sample(c(1,-1), 300, replace = TRUE), 15, 20)

# run
result <- simu.GEBVO(fitvalue, geno.t = geno.test, marker = marker.test,
geno.c = geno.candidate, nprog = 5, nsele = 10, ngen = 5, nrep = 5)

# summary for the best individuals
output <- output.best(result)
output

IPLGP documentation built on April 6, 2023, 5:23 p.m.