beta.dosage: Estimates pairwise kinships and individual inbreeding...

beta.dosageR Documentation

Estimates pairwise kinships and individual inbreeding coefficients from dosage data

Description

Estimates pairwise kinships (coancestries) and individual inbreeding coefficient using Weir and Goudet (2017) beta estimator.

Usage

beta.dosage(dos,inb=TRUE,Mb=FALSE,matching=FALSE)

kas.dosage(dos, inb = TRUE, Mb = FALSE, matching = FALSE)

Arguments

dos

A matrix of 0, 1 and 2s with loci (SNPs) in columns and individuals in rows. Missing values are allowed

inb

whether individual inbreeding coefficient should be estimated (rather than self-coancestries)

Mb

whether to output the mean matching of off-diagonal elements

matching

if matching=FALSE, dos is a (ni x nl) dosage matrix; if matching=TRUE, dos is a (ni x ni) matrix of matching proportions, as obtained from a call to the matching function

Details

This function is written for dosage data, i.e., how many doses of an allele (0, 1 or 2) an individual carries. It should be use for bi-allelic markers only (e.g. SNPs), although you might "force" a k multiallelic locus to k biallelic loci (see fstat2dos).

Matching proportions can be obtained by the following equation: M=\beta*(1-Mb)+Mb

By default (inb=TRUE) the inbreeding coefficient is returned on the main diagonal. With inb=FALSE, self coancestries are reported.

Twice the betas with self-coancestries on the diagonal gives the Genomic Relationship Matrix (GRM)

Following a suggestion from Olivier Hardy, missing data are removed from the estimation procedure, rather than imputed (this is taken care off automatically)

Value

if Mb=FALSE, a matrix of pairwise kinships and inbreeding coefficients (if inb=TRUE) or self-coancestries (inb=FALSE); if Mb=TRUE, a list with elements inb (whether inbreeding coefficients rather than kinships should be returned on the main diagonal), MB (the average off-diagonal matching) and betas the kinships or inbreeding coefficients.

Author(s)

Jerome Goudet jerome.goudet@unil.ch

References

Weir, BS and Goudet J. 2017 A Unified Characterization of Population Structure and Relatedness. Genetics (2017) 206:2085

Goudet, J., Kay, T. and Weir BS. 2018 How to estimate kinship. Molecular Ecology 27:4121.

Examples

## Not run: 
 dos<-matrix(sample(0:2,size=10000,replace=TRUE),ncol=100)
 beta.dosage(dos,inb=TRUE)
 
 #matrix of kinship/inbreeding coeff
 data(gtrunchier)
 beta.dosage(fstat2dos(gtrunchier[,-c(1:2)]))
 
 #individual inbreeding coefficients
 dat<-sim.genot(size=100,nbloc=100,nbal=20,mig=0.01,f=c(0,0.3,0.7))
 hist(diag(beta.dosage(fstat2dos(dat[,-1]))),breaks=-10:100/100,main="",xlab="",ylab="")
 abline(v=c(0.0,0.3,0.7),col="red")
 #only 20 loci
 hist(diag(beta.dosage(fstat2dos(dat[,2:21]))),breaks=-5:20/20,main="",xlab="",ylab="")
 abline(v=c(0.0,0.3,0.7),col="red")
 

## End(Not run)


jgx65/hierfstat documentation built on April 20, 2023, 8:34 a.m.