ld.weights: LD weights

In rres: Realized Relatedness Estimation and Simulation

Description

ld.weights computes LD weights for all markers, which is subsequently used to compute LD weighted GRM.

Usage

ld.weights(data, input.genotype = TRUE)

Arguments

data	numeric matrix.
input.genotype	logical.

Details

data can either be the subject by marker numeric genotype matrix (with 0, 1 or 2 coding), or the matrix of marker genotypic correlations. The default option is to input genotype matrix.

Value

A numeric vector of weights. Note that the sum of weights is not constrained to be 1. They should be scaled appropriately before computing the LD weighted GRM.

Examples

# simulate genotypes of 500 individuals at 100 markers
nsnp = 100 # number of SNPs
freq = runif(nsnp, 0.05, 0.95)
nhaplo = 1000 # number of founder haplotypes
haplo.mat = sim.haplotype(freq, nhaplo)
geno.mat = t(sapply(c(1:500), function(x) 4 - haplo.mat[2*x-1,] - haplo.mat[2*x,]))

# compute unconstrained LD weights
ld.weights(geno.mat)

rres documentation built on May 2, 2019, 2:51 p.m.