snpgdsIndivBeta {SNPRelate} | R Documentation

## Individual inbreeding and relatedness estimation (beta estimator)

### Description

Calculate individual inbreeding and relatedness estimation (beta estimator) using SNP genotype data.

### Usage

    snpgdsIndivBeta(gdsobj, sample.id=NULL, snp.id=NULL, autosome.only=TRUE,
        remove.monosnp=TRUE, maf=NaN, missing.rate=NaN, method=c("weighted"),
        inbreeding=TRUE, num.thread=1L, with.id=TRUE, useMatrix=FALSE, verbose=TRUE)
    snpgdsIndivBetaRel(beta, beta_rel, 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
`method` | "weighted" estimator
`inbreeding` | `TRUE`, the diagonal is a vector of inbreeding coefficients; otherwise, individual variance estimates
`num.thread` | the number of (CPU) cores used; if `NA`, detect the number of cores automatically
`with.id` | if `TRUE`, the returned value with `sample.id` and `sample.id`
`useMatrix` | if `TRUE`, use `Matrix::dspMatrix` to store the output square matrix to save memory
`beta` | the object returned from `snpgdsIndivBeta()`
`beta_rel` | the beta-based matrix is generated relative to `beta_rel`
`verbose` | if `TRUE`, show information

### Value

Return a list if `with.id = TRUE`:

`sample.id` | the sample ids used in the analysis
`snp.id` | the SNP ids used in the analysis
`inbreeding` | a logical value; `TRUE`, the diagonal is a vector of inbreeding coefficients; otherwise, individual variance estimates
`beta` | beta estimates
`avg_val` | the average of M_B among all loci, it could be used to calculate each M_ij

If `with.id = FALSE`, this function returns the genetic relationship matrix without sample and SNP IDs.

### Author(s)

Xiuwen Zheng

### References

Weir BS, Zheng X. SNPs and SNVs in Forensic Science. Forensic Science International: Genetics Supplement Series. 2015. doi:10.1016/j.fsigss.2015.09.106

Weir BS, Goudet J. A Unified Characterization of Population Structure and Relatedness. Genetics. 2017 Aug;206(4):2085-2103. doi: 10.1534/genetics.116.198424.

### See Also

`snpgdsGRM`, `snpgdsIndInb`, `snpgdsFst`

### Examples

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

    b <- snpgdsIndivBeta(genofile, inbreeding=FALSE)
    b$beta[1:10, 1:10]

    z <- snpgdsIndivBetaRel(b, min(b$beta))

    # close the file
    snpgdsClose(genofile)

[Package SNPRelate version 1.24.0 Index]