snpgdsIBS {SNPRelate} | R Documentation

## Identity-By-State (IBS) proportion

### Description

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

### Usage

    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)

### 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
`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

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.

### Value

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"

### Author(s)

Xiuwen Zheng

### See Also

`snpgdsIBSNum`

### Examples

    # 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)

[Package SNPRelate version 1.18.1 Index]