plot.hlaAttrBagObj: Plot a "hlaAttrBagObj" object

In HIBAG: HIBAG -- HLA Genotype Imputation with Attribute Bagging

Description

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

Usage

## S3 method for class 'hlaAttrBagObj'
plot(x, xlab=NULL, ylab=NULL,
	locus.color="red", locus.lty=2, locus.cex=1.25,
	assembly=c("auto", "hg18", "hg19", "unknown"), ...)

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: "hg19" (default), "hg18", "auto" refers to "hg19"
...	further arguments passed to or from other methods

Author(s)

Xiuwen Zheng

See Also

print.hlaAttrBagObj, summary.hlaAttrBagObj

Examples

# load HLA types and SNP genotypes
data(HLA_Type_Table, package="HIBAG")
data(HapMap_CEU_Geno, package="HIBAG")

# 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)

HIBAG documentation built on May 2, 2019, 4:50 p.m.