HIBAG (version 1.8.3)

plot.hlaAttrBagObj: Plot a HIBAG model

Description

To show a scatterplot of the numbers of individual classifiers and SNP positions.

Usage

"plot"(x, xlab=NULL, ylab=NULL, locus.color="red", locus.lty=2, locus.cex=1.25, assembly="auto", ...)
"plot"(x, ...)

Arguments

x

an object of hlaAttrBagObj

xlab

the label of X-axis

ylab

the label of Y-axis

locus.color

the color of text and line for HLA locus

locus.lty

the type of line for HLA locus

locus.cex

the font size of HLA locus

assembly

the human genome reference: "hg18", "hg19" (default), "hg20"; "auto" refers to "hg19"; "auto-silent" refers to "hg19" without any warning

...

further arguments passed to or from other methods

Value

See Also

print.hlaAttrBagObj, summary.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)
plot(model)