snpgdsIBDMoM: PLINK method of moment (MoM) for the Identity-By-Descent...
In SNPRelate: Parallel Computing Toolset for Genome-Wide Association Studies (GWAS)

Description Usage Arguments Details Value Author(s) References See Also Examples

Calculate three IBD coefficients for non-inbred individual pairs by PLINK method of moment (MoM).

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snpgdsIBDMoM(gdsobj, sample.id=NULL, snp.id=NULL, autosome.only=TRUE,
	remove.monosnp=TRUE, maf=NaN, missing.rate=NaN, allele.freq=NULL,
	kinship=FALSE, kinship.constraint=FALSE, num.thread=1, verbose=TRUE)

`gdsobj`	a GDS file object (`gds.class`)
`sample.id`	a vector of sample id specifying selected samples; if NULL, all samples are used
`snp.id`	a vector of snp id specifying selected SNPs; if NULL, all SNPs are used
`autosome.only`	if TRUE, use autosomal SNPs only
`remove.monosnp`	if TRUE, remove monomorphic SNPs
`maf`	to use the SNPs with ">= maf" only; if NaN, no MAF threshold
`missing.rate`	to use the SNPs with "<= missing.rate" only; if NaN, no missing threshold
`allele.freq`	to specify the allele frequencies; if NULL, determine the allele frequencies from `gdsobj` using the specified samples
`kinship`	if `TRUE`, output the estimated kinship coefficients
`kinship.constraint`	if TRUE, constrict IBD coefficients ($k_0,k_1,k_2$) in the geneloical region ($2 k_0 k_1 >= k_2^2$)
`num.thread`	the number of CPU cores used
`verbose`	if TRUE, show information

PLINK IBD estimator is a moment estimator, and it is computationally efficient relative to MLE method. In the PLINK method of moment, a correction factor based on allele counts is used to adjust for sampling. However, if allele frequencies are specified, no correction factor is conducted since the specified allele frequencies are assumed to be known without sampling.

The minor allele frequency and missing rate for each SNP passed in snp.id are calculated over all the samples in sample.id.

Return a list:

`sample.id`	the sample ids used in the analysis
`snp.id`	the SNP ids used in the analysis
`k0`	IBD coefficient, the probability of sharing ZERO IBD
`k1`	IBD coefficient, the probability of sharing ONE IBD
`kinship`	the estimated kinship coefficients, if the parameter `kinship=TRUE`

Xiuwen Zheng

Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ & Sham PC. 2007. PLINK: a toolset for whole-genome association and population-based linkage analysis. American Journal of Human Genetics, 81.

snpgdsIBDMLE, snpgdsIBDMLELogLik

# open an example dataset (HapMap)
genofile <- openfn.gds(snpgdsExampleFileName())

#########################################################
# CEU population

CEU.id <- read.gdsn(index.gdsn(genofile, "sample.id"))[
	read.gdsn(index.gdsn(genofile, "sample.annot/pop.group"))=="CEU"]
pibd <- snpgdsIBDMoM(genofile, sample.id=CEU.id)
names(pibd)

flag <- lower.tri(pibd$k0)
plot(NaN, xlim=c(0,1), ylim=c(0,1), xlab="k0", ylab="k1")
lines(c(0,1), c(1,0), col="red", lty=3)
points(pibd$k0[flag], pibd$k1[flag])

# select a set of pairs of individuals
d <- snpgdsIBDSelection(pibd, kinship.cutoff=1/8)
head(d)


#########################################################
# YRI population

YRI.id <- read.gdsn(index.gdsn(genofile, "sample.id"))[
	read.gdsn(index.gdsn(genofile, "sample.annot/pop.group"))=="YRI"]
pibd <- snpgdsIBDMoM(genofile, sample.id=YRI.id)
flag <- lower.tri(pibd$k0)
plot(NaN, xlim=c(0,1), ylim=c(0,1), xlab="k0", ylab="k1")
lines(c(0,1), c(1,0), col="red", lty=3)
points(pibd$k0[flag], pibd$k1[flag])


# specify the allele frequencies
afreq <- snpgdsSNPRateFreq(genofile, sample.id=YRI.id)$AlleleFreq
aibd <- snpgdsIBDMoM(genofile, sample.id=YRI.id, allele.freq=afreq)
flag <- lower.tri(aibd$k0)
plot(NaN, xlim=c(0,1), ylim=c(0,1), xlab="k0", ylab="k1")
lines(c(0,1), c(1,0), col="red", lty=3)
points(aibd$k0[flag], aibd$k1[flag])

# analysis on a subset
subibd <- snpgdsIBDMoM(genofile, sample.id=YRI.id[1:25], allele.freq=afreq)
summary(c(subibd$k0 - aibd$k0[1:25, 1:25]))
# ZERO
summary(c(subibd$k1 - aibd$k1[1:25, 1:25]))
# ZERO


# close the genotype file
closefn.gds(genofile)