Run genomic prediction on all genotypes, output predicted values
compute_GP_allGeno.RdRun genomic prediction on all genotypes, output predicted values
Usage
compute_GP_allGeno(
geno,
pheno,
traits,
GP.method,
runCV = FALSE,
testSetGID = NULL,
nreps = 10,
nfolds = 10,
h = 1,
nb.mtry = 10,
nIter = 6000,
burnIn = 1000,
ntree = 100,
p2d.temp = NULL,
nb.cores = 1,
p2f.stats.cv = NULL,
p2f.pred = NULL,
verbose = 1
)Arguments
- geno
genomic data with genotypes in row (GID in rownames) and marker in columns. Values should be column centered and scaled.
- pheno
phenotypic data with genotypes in row (in GID column) and traits in columns
- traits
character vector of trait names, must correspond to
phenocolumn names- GP.method
character vector of genomic prediction methods to use, must be one of "rrBLUP", "RKHS", "BayesA", "BayesB"
- runCV
logical, if TRUE, run cross-validation on the common genotypes in
phenoandgeno, default is FALSE- testSetGID
GID of the test set genotypes, if NULL, will provide predicted genotypic values for all genotypes in
geno- nreps
number of repetitions for cross-validation, default is 10
- nfolds
number of folds for cross-validation, default is 10
- h
bandwith parameter for RKHS, default is 1.
- nb.mtry
number of randomly selected variables at each split for RandomForest, default is 10
- nIter
number of iterations for RKHS, default is 6000
- burnIn
number of burn-in iterations for RKHS, default is 1000
- ntree
number of trees for RandomForest, default is 100
- p2d.temp
path to directory to export temporary genomic prediction results, default is NULL (could cause error in parallelization if NULL).
- nb.cores
number of cores to parallelize the computation, default is 1 (no parallelization)
- p2f.stats.cv
path to file to export cross-validation genomic prediction results, default is NULL
- p2f.pred
path to file to export genotypic values from genomic prediction, default is NULL
- verbose
integer, level of verbosity, default is 1