hlaGenoLD: Composite Linkage Disequilibrium

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

Description

To calculate composite linkage disequilibrium (r2) between HLA locus and SNP markers.

Usage

hlaGenoLD(hla, geno)

Arguments

hla	an object of hlaAlleleClass
geno	an object of hlaSNPGenoClass, or a vector or matrix for SNP data

Value

Return a vector of linkage disequilibrium (r2) for each SNP marker.

Author(s)

Xiuwen Zheng

References

Weir BS, Cockerham CC: Complete characterization of disequilibrium at two loci; in Feldman MW (ed): Mathematical Evolutionary Theory. Princeton, NJ: Princeton University Press, 1989.

Zaykin, D. V., Pudovkin, A., and Weir, B. S. (2008). Correlation-based inference for linkage disequilibrium with multiple alleles. Genetics 180, 533-545.

Examples

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

# plot linkage disequilibrium
ymax <- 0.16
plot(NaN, NaN, xlab="SNP Position (in KB)",
	ylab="Composite Linkage Disequilibrium (r2)",
	xlim=range(HapMap_CEU_Geno$snp.position)/1000, ylim=c(0, ymax),
	main="Major Histocompatibility Complex")

hla.list <- c("A", "C", "DQA1")
col.list <- 1:3

# for-loop
for (i in 1:3)
{
	hla.id <- hla.list[i]

	# make a "hlaAlleleClass" object
	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")

	# linkage disequilibrium between HLA locus and SNP markers
	ld <- hlaGenoLD(hla, HapMap_CEU_Geno)

	# draw
	points(HapMap_CEU_Geno$snp.position/1000, ld, pch="*", col=i)
	x <- (hla$pos.start/1000 + hla$pos.end/1000)/2
	abline(v=x, col=col.list[i], lty=3, lwd=2.5)
	points(x, ymax, pch=25, col=7, bg=col.list[i], cex=1.5)
}
legend("topleft", col=col.list, pt.bg=col.list, text.col=col.list, pch=25,
	legend=paste("HLA -", hla.list))

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