snpgdsIBDMoM: PLINK method of moment (MoM) for the Identity-By-Descent...

View source: R/IBD.R

snpgdsIBDMoMR Documentation

PLINK method of moment (MoM) for the Identity-By-Descent (IBD) Analysis

Description

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

Usage

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=1L, useMatrix=FALSE,
    verbose=TRUE)

Arguments

gdsobj

an object of class SNPGDSFileClass, a SNP GDS file

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; if it is a numeric or character value, keep SNPs according to the specified chromosome

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; if snp.id is specified, allele.freq should have the same order as snp.id

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; if NA, detect the number of cores automatically

useMatrix

if TRUE, use Matrix::dspMatrix to store the output square matrix to save memory

verbose

if TRUE, show information

Details

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.

Value

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

Author(s)

Xiuwen Zheng

References

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.

See Also

snpgdsIBDMLE, snpgdsIBDMLELogLik

Examples

# open an example dataset (HapMap)
genofile <- snpgdsOpen(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
snpgdsClose(genofile)

zhengxwen/SNPRelate documentation built on March 16, 2024, 1:44 p.m.