calcGRM: Function to calculate genomic relationship matrix (GRM)

In RAINBOWR: Genome-Wide Association Study with SNP-Set Methods

Function to calculate genomic relationship matrix (GRM)

Description

Function to calculate genomic relationship matrix (GRM)

Usage

calcGRM(
  genoMat,
  methodGRM = "addNOIA",
  subpop = NULL,
  kernel.h = "tuned",
  returnWMat = FALSE,
  probaa = NULL,
  probAa = NULL,
  batchSize = NULL,
  n.core = 1
)

Arguments

genoMat	A N \times M matrix of marker genotype
methodGRM	Method to calculate genomic relationship matrix (GRM). We offer the following methods; "addNOIA", "domNOIA", "A.mat", "linear", "gaussian", "exponential", "correlation". For NOIA methods, please refer to Vitezica et al. 2017.
subpop	Sub-population names corresponding to each individual. By utilizing 'subpop' argument, you can consider the difference of allele frequencies between sub-populations when computing the genomic relationship matrix. This argument is only valid when NOIA methods are selected.
kernel.h	The hyper parameter for gaussian or exponential kernel. If kernel.h = "tuned", this hyper parameter is calculated as the median of off-diagonals of distance matrix of genotype data.
returnWMat	If this argument is TRUE, we will return W matrix instead of GRM. Here, W satisfies GRM = W W ^ {T}. W corresponds to H matix in Vitezica et al. 2017.
probaa	Probability of being homozygous for the reference allele for each marker. If NULL (default), it will be calculated from genoMat.
probAa	Probability of being heterozygous for the reference and alternative alleles for each marker If NULL (default), it will be calculated from genoMat.
batchSize	Split marker genotype data into subsets consisting of 'batchSize' SNPs, and compute GRM. If NULL, all the markers will be used for the computation at a time. We recommend using this argument when the total number of markers is too large.
n.core	Setting n.core > 1 will enable parallel execution on a machine with multiple cores. This argument is only valid 'batchSize' is not 'NULL'.

Value

genomic relationship matrix (GRM)

References

Vitezica, Z.G., Legarra, A., Toro, M.A. and Varona, L. (2017) Orthogonal Estimates of Variances for Additive, Dominance, and Epistatic Effects in Populations. Genetics. 206(3): 1297-1307.

Endelman, J.B. and Jannink, J.L. (2012) Shrinkage Estimation of the Realized Relationship Matrix. G3 Genes, Genomes, Genet. 2(11): 1405-1413.

RAINBOWR documentation built on June 8, 2025, 1:54 p.m.