snpgdsIBS: Identity-By-State (IBS) proportion
In SNPRelate: Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

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

Calculate the fraction of identity by state for each pair of samples

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snpgdsIBS(gdsobj, sample.id=NULL, snp.id=NULL, autosome.only=TRUE,
    remove.monosnp=TRUE, maf=NaN, missing.rate=NaN, num.thread=1L,
    useMatrix=FALSE, verbose=TRUE)

`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
`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

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

The values of the IBS matrix range from ZERO to ONE, and it is defined as the average of 1 - | g_{1,i} - g_{2,i} | / 2 across the genome for the first and second individuals and SNP i.

Return a list (class "snpgdsIBSClass"):

`sample.id`	the sample ids used in the analysis
`snp.id`	the SNP ids used in the analysis
`ibs`	a matrix of IBS proportion, "# of samples" x "# of samples"

Xiuwen Zheng

snpgdsIBSNum

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

# perform identity-by-state calculations
ibs <- snpgdsIBS(genofile)

# perform multidimensional scaling analysis on
# the genome-wide IBS pairwise distances:
loc <- cmdscale(1 - ibs$ibs, k = 2)
x <- loc[, 1]; y <- loc[, 2]
race <- as.factor(read.gdsn(index.gdsn(genofile, "sample.annot/pop.group")))
plot(x, y, col=race, xlab = "", ylab = "", main = "cmdscale(IBS Distance)")
legend("topleft", legend=levels(race), text.col=1:nlevels(race))

# close the file
snpgdsClose(genofile)

Loading required package: gdsfmt
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Sun Jan 21 05:32:11 2018    (internal increment: 13056)

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Sun Jan 21 05:32:11 2018    Done.