set.seed(311)
pheno <- data.frame(Yield = rnorm(10,200,5),Height=rnorm(10,100,1))
rownames(pheno) <- letters[1:10]
geno <- matrix(sample(c("A","A/B","B",NA),size=120,replace=TRUE,
prob=c(0.6,0.2,0.1,0.1)),nrow=10)
rownames(geno) <- letters[1:10]
colnames(geno) <- paste("M",1:12,sep="")
# one SNP is not mapped (M5)
map <- data.frame(chr=rep(1:3,each=4),pos=rep(1:12))
map <- map[-5,]
rownames(map) <- paste("M",c(1:4,6:12),sep="")
gp <- create.gpData(pheno=pheno,geno=geno,map=map)
summary(gp)
#new phenotypic data
newPheno <- data.frame(Yield=200,Height=100,row.names="newLine")
# simulating genotypic data
newGeno <- matrix(sample(c("A","A/B","B"),ncol(gp$geno),replace=TRUE),nrow=1)
rownames(newGeno) <- "newLine"
# new pedigree
newPedigree <- create.pedigree(ID="newLine",Par1=0,Par2=0,gener=0)
gp2 <- add.individuals(gp,pheno=newPheno,geno=newGeno,pedigree=newPedigree)
## Not run: ------------------------------------
# # add one new DH line to maize data
# library(synbreedData)
# data(maize)
# newDHpheno <- data.frame(Trait=1000,row.names="newDH")
# # simulating genotypic data
# newDHgeno <- matrix(sample(c(0,1),ncol(maize$geno),replace=TRUE),nrow=1)
# rownames(newDHgeno) <- "newDH"
# # new pedigree
# newDHpedigree <- create.pedigree(ID="newDH",Par1=0,Par2=0,gener=0)
# # new covar information
# newDHcovar <- data.frame(family=NA,DH=1,tbv=1000,row.names="newDH")
#
# # add individual
# maize2 <- add.individuals(maize,newDHpheno,newDHgeno,newDHpedigree,newDHcovar)
# summary(maize2)
## ---------------------------------------------
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