| Type: | Package |
| Title: | Genetic Algorithm Assisted Genomic Best Liner Unbiased Prediction |
| Version: | 1.0 |
| Description: | Performs genetic algorithm (Scrucca, L (2013) <doi:10.18637/jss.v053.i04>) assisted genomic best liner unbiased prediction for genomic selection. It also provides a binning method in natural population for genomic selection under the principle of linkage disequilibrium for dimensional reduction. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Depends: | R (≥ 4.1.0) |
| Imports: | GA, foreach, doParallel |
| NeedsCompilation: | no |
| Packaged: | 2023-09-05 02:39:04 UTC; Dell |
| Repository: | CRAN |
| Date/Publication: | 2023-09-05 16:50:08 UTC |
| Maintainer: | Yuxiang Zhang <yuxiangzhang_99@foxmail.com> |
| Author: | Yuxiang Zhang [aut, cre], Yang Xu [aut], Yanru Cui [ctb], Chenwu Xu [ctb], Shizhong Xu [ctb] |
Binning Genotypes for Dimensional Reduction
Description
Binning the original genotypes into bins for dimensional reduction under the principle of linkage disequilibrium.
Usage
bin(genotype = genotype, binvar = 0.15)
Arguments
genotype |
a matrix for genotypes in numeric format, coded as 1, 0 and -1, with individuals in rows and markers in cols. |
binvar |
a hyper-parameter between 0 and 1, the closer to 0, the fewer bins yields. Users can choose binvar based on the required number of bins, default is 0.15. |
Value
A list with following information is returned: $bins_genotypes binned genotypes $bins_range start and stop of each bin
Examples
## load example data from GAGBLUP package
data(genotype)
## binning genotypes
bins <- bin(genotype,0.2)
binned genotypes
Description
Binned genotypes of 410 maize hybrids.
Usage
bins
Format
A data frame with 410 rows and 810 variables.
Genetic algorithm assisted genomic best liner unbiased prediction for genomic selection
Description
Performs genomic selection with genetic algorithm assisted genomic best liner unbiased prediction
Usage
gagblup(
genotype,
phenotype,
fit_fun = "HAT",
maxiter = 2000,
nfold = 10,
nTimes = 1,
seed = 123,
n_core = 1
)
Arguments
genotype |
a matrix for genotypes in numeric format, with individuals in rows and markers in cols. |
phenotype |
a vector of phenotype, missing (NA) values are not allowed. |
fit_fun |
the fitness function. There are four options: fitness = "AIC"/"BIC"/"FIT"/"HAT", default is "HAT" |
maxiter |
max number of iterations for GAGBLUP, default is 2000 |
nfold |
the number of folds. Default is 10. |
nTimes |
the number of independent replicates for the cross-validation. Default is 1. |
seed |
the random number. Default is 123. |
n_core |
the number of CPU to be used, default is 1. |
Value
A list with following information is returned: $R2 the squared pearson correlation coefficient between the true value and the predicted value, $predicted_value the predicted value and the true value of the phenotype, $marker_selection a vector of the selected markers, with 1 indicates selected, 0 indicates not selected.
Examples
## load example data from GAGBLUP package
data(phenotype)
data(bins)
phenotype <- phenotype[1:200,3]
result <- gagblup(bins[1:200,],phenotype,fit_fun='HAT',maxiter=1,nfold=2,nTimes=1,seed=123,n_core=1)
Genotype in Numeric Format
Description
Genotypic data of 410 maize hybrids with 4906 SNPs.
Usage
genotype
Format
A data frame with 410 rows and 4906 variables.
Phenotypic data of 410 hybrids
Description
This dataset contains phenotypic data of 410 hybrids for grain yield in maize.
Usage
phenotype
Format
A data frame with 410 rows and 3 variables:
MThe names of male parents.
FThe names of female parents.
GYThe grain yield of hybrids.