snpgdsIndInbCoef {SNPRelate} | R Documentation

## Individual Inbreeding Coefficient

### Description

To calculate an individual inbreeding coefficient using SNP genotype data

### Usage

    snpgdsIndInbCoef(x, p, method = c("mom.weir", "mom.visscher", "mle"),
        reltol=.Machine$double.eps^0.75)

### Arguments

`x` | SNP genotypes
`p` | allele frequencies
`method` | see details
`reltol` | relative convergence tolerance used in MLE; the algorithm stops if it is unable to reduce the value of log likelihood by a factor of $reltol * (abs(log likelihood with the initial parameters) + reltol)$ at a step.

### Details

The `method` can be: `"mom.weir"`: a modified Visscher's estimator, proposed by Bruce Weir; `"mom.visscher"`: Visscher's estimator described in Yang et al. (2010); `"mle"`: the maximum likelihood estimation.

### Value

Return estimated inbreeding coefficient.

### Author(s)

Xiuwen Zheng

### References

Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM. 2010. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 42(7):565-9. Epub 2010 Jun 20.

### Examples

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

    chr1 <- read.gdsn(index.gdsn(genofile, "snp.id"))[
        read.gdsn(index.gdsn(genofile, "snp.chromosome"))==1]
    chr1idx <- match(chr1, read.gdsn(index.gdsn(genofile, "snp.id")))

    AF <- snpgdsSNPRateFreq(genofile)
    g <- read.gdsn(index.gdsn(genofile, "genotype"), start=c(1,1), count=c(-1,1))

    snpgdsIndInbCoef(g[chr1idx], AF$AlleleFreq[chr1idx], method="mom.weir")
    snpgdsIndInbCoef(g[chr1idx], AF$AlleleFreq[chr1idx], method="mom.visscher")
    snpgdsIndInbCoef(g[chr1idx], AF$AlleleFreq[chr1idx], method="mle")

    # close the genotype file
    snpgdsClose(genofile)

[Package SNPRelate version 1.24.0 Index]