Calculate a relatedness matrix

Given a matrix of genotypes, this function estimates the genetic relatedness matrix (GRM, also known as the RRM, see Hayes et al. 2009, doi:10.1017/S0016672308009981 ) among the subjects: \(\frac{1}{p}(XX^T)\), where X is standardized.

Usage

relatedness_mat(X, std = TRUE, ns = NULL)

Arguments

X

An n x p numeric matrix of genotypes (from fully-imputed data). Can be a filebacked big.matrix object. Note: This matrix should not include non-genetic features.

std

Logical: should X be standardized? If you set this to FALSE, you should have a good reason for doing so, as standardization is a best practice.

ns

Optional vector of values indicating the indices of nonsingular features. Note: If a filebacked big.matrix is passed to X along with a non-null ns, a temporary deep copy will be created.

Value

An n x n numeric matrix capturing the genomic relatedness of the samples represented in X. In our notation, we call this matrix K for 'kinship'; this is also known as the GRM or RRM.

Examples

RRM <- relatedness_mat(X = admix$X)
RRM[1:5, 1:5]
#>             [,1]        [,2]        [,3]        [,4]        [,5]
#> [1,]  0.81268908 -0.09098097 -0.07888910  0.06770613  0.08311777
#> [2,] -0.09098097  0.81764801  0.20480021  0.02112812 -0.02640295
#> [3,] -0.07888910  0.20480021  0.82177986 -0.02864226  0.18693970
#> [4,]  0.06770613  0.02112812 -0.02864226  0.89327266 -0.03541470
#> [5,]  0.08311777 -0.02640295  0.18693970 -0.03541470  0.79589686