# make a "hlaAlleleClass" object
hla.id <- "A"
hla <- hlaAllele(HLA_Type_Table$sample.id,
H1 = HLA_Type_Table[, paste(hla.id, ".1", sep="")],
H2 = HLA_Type_Table[, paste(hla.id, ".2", sep="")],
locus=hla.id, assembly="hg19")
# SNP predictors within the flanking region on each side
region <- 500 # kb
snpid <- hlaFlankingSNP(HapMap_CEU_Geno$snp.id, HapMap_CEU_Geno$snp.position,
hla.id, region*1000, assembly="hg19")
length(snpid) # 275
# training genotypes
train.geno <- hlaGenoSubset(HapMap_CEU_Geno,
snp.sel = match(snpid, HapMap_CEU_Geno$snp.id))
# train a HIBAG model
set.seed(100)
m1 <- hlaAttrBagging(hla, train.geno, nclassifier=1)
m2 <- hlaAttrBagging(hla, train.geno, nclassifier=1)
m1.obj <- hlaModelToObj(m1)
m2.obj <- hlaModelToObj(m2)
m.obj <- hlaCombineModelObj(m1.obj, m2.obj)
summary(m.obj)
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