HIBAG (version 1.8.3)

print.hlaAttrBagClass: Summarize a ``hlaAttrBagClass'' or ``hlaAttrBagObj'' object.

Description

Summarize an object of hlaAttrBagClass or hlaAttrBagObj.

Usage

"print"(x, ...)
"print"(x, ...)
"summary"(object, show=TRUE, ...)
"summary"(object, show=TRUE, ...)

Arguments

x

an object of hlaAttrBagClass or hlaAttrBagObj

object

an object of hlaAttrBagClass or hlaAttrBagObj

show

if TRUE, show information

...

further arguments passed to or from other methods

Value

print returns NULL.summary.hlaAttrBagClass and summary.hlaAttrBagObj return a list:

num.classifier

the total number of classifiers

num.snp

the total number of SNPs

snp.id

SNP IDs

snp.position

SNP position in basepair

snp.hist

the number of classifier for each SNP, and it could be used for SNP importance

info

a data.frame for the average number of SNPs (num.snp), haplotypes (num.haplo), out-of-bag accuracies (accuracy) among all classifiers: mean, standard deviation, min, max

See Also

plot.hlaAttrBagClass, plot.hlaAttrBagObj

Examples

# make a "hlaAlleleClass" object
hla.id <- "C"
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")

# training genotypes
region <- 100   # kb
snpid <- hlaFlankingSNP(HapMap_CEU_Geno$snp.id, HapMap_CEU_Geno$snp.position,
    hla.id, region*1000, assembly="hg19")
train.geno <- hlaGenoSubset(HapMap_CEU_Geno,
    snp.sel = match(snpid, HapMap_CEU_Geno$snp.id))

# train a HIBAG model
set.seed(1000)
# please use "nclassifier=100" when you use HIBAG for real data
model <- hlaAttrBagging(hla, train.geno, nclassifier=2, verbose.detail=TRUE)
print(model)