output.best {IPLGP} | R Documentation |
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