relatedness_mat: Calculate a relatedness matrix

In plmmr: Penalized Linear Mixed Models for Correlated Data

Calculate a relatedness matrix

Description

Given a matrix of genotypes, this function estimates the genetic relatedness matrix (GRM, also known as the RRM, see Hayes et al. 2009, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1017/S0016672308009981")}) among the subjects: XX'/p, where X is standardized.

Usage

relatedness_mat(X, std = TRUE, fbm = FALSE, ns = NULL, ...)

Arguments

X	An n x p numeric matrix of genotypes (from fully-imputed data). Note: This matrix should not include non-genetic features.
std	Logical: should X be standardized? If you set this to FALSE (which can only be done if data are stored in memory), you should have a good reason for doing so, as standardization is a best practice.
fbm	Logical: is X stored as an FBM? Defaults to FALSE
ns	Optional vector of values indicating the indices of nonsingular features
...	Other optional arguments to bigstatsr::bigapply() (like ncores = ...)

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]

plmmr documentation built on April 4, 2025, 12:19 a.m.