snpgdsIndivBeta: Individual inbreeding and relatedness estimation (beta...
In zhengxwen/SNPRelate: Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

snpgdsIndivBeta

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.

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)

zhengxwen/SNPRelate documentation built on April 16, 2024, 8:42 a.m.