IPLGP
In this package, we provide a tool to select parental lines for multiple traits in plant breeding. To confirm the potential of a set of parental lines, this package provides two useful tools. One is D-score, which is a new criteria we proposed in our study for determine the potential of a set of parental line. The other is the simulation test of the breeding process. There are three strategy in our simulation test, which is (i) GEBV-O considers only genomic estimated breeding values (GEBVs) of the candidate individuals; (ii) GD-O considers only genomic diversity (GD) of the candidate individuals; and (iii) GEBV-GD considers both GEBV and GD.
Installation
IPLGP can be installed form GitHub by the following command:
# library(devtools)
install_github("py-chung/IPLGP", dependencies = TRUE, force = TRUE)
And IPLGP can be installed form CRAN by the following command:
install.packages("IPLGP")
Main functions
GA.Dscore()Fonction for getting a set with highest D-score by genetic algorithm.GBLUP.fit()Fonction for getting the fitting values of a set of individuals by GBLUP.geno.d()Fonction for getting the design matrix and kinship matrix of dominance effects.phe.sd()Fonction for getting the standardize phenotypic values.simu.gamete()Fonction for simulating the genotype of a gamete.simu.GDO()Fonction for simulating the progeny with GD-O strategy.simu.GEBVO()Fonction for simulating the progeny with GEBV-O strategy.simu.GEBVGD()Fonction for simulating the progeny with GEBV-GD strategy.output.best()Fonction for obtaining the GEBV average curves and the summary statistics form the output of simulation test.output.gain()Fonction for obtaining the genetic gain average for each target trait form the output of simulation test.
More information can be seen in the following file:
Package ‘IPLGP’
Example dataset
The example dataset is provided to test this package. The rice genome dataset we used in our study was presented in Spindel et al. (2015). The data was processed by us and contains 328 individuals and 10772 SNPs. The SNP data and phenotype data can be downloaded from GitHub by the following command:
load(url("https://github.com/py-chung/IPLGP/raw/main/inst/extdata/snp.trop.RDATA"))
load(url("https://github.com/py-chung/IPLGP/raw/main/inst/extdata/phe.trop.RDATA"))Or it can be loaded form package after install IPLGP by the following command:
load(system.file("extdata", "snp.trop.RDATA", package = "IPLGP"))
load(system.file("extdata", "phe.trop.RDATA", package = "IPLGP"))
Citing this package
For more imformation about our method, please check our published article:
- Chung PY, Liao CT. 2020. Identification of superior parental lines for biparental crossing via genomic prediction. PLoS ONE 15(12):e0243159. doi:10.1371/journal.pone.0243159
If you use IPLGP in your research, we would appreciate your citation of the study article.