View source: R/functions_for_RGWAS.R
adjustGRM | R Documentation |
Function to adjust genomic relationship matrix (GRM) with subpopulations
adjustGRM(
y,
X = NULL,
ZETA,
subpopInfo = NULL,
nSubpop = 5,
nPcsFindCluster = 10,
include.epistasis = FALSE,
package.MM = "gaston"
)
y |
A |
X |
A |
ZETA |
A list of variance matrices and its design matrices of random effects. You can use only one kernel matrix for this function. For example, ZETA = list(A = list(Z = Z.A, K = K.A)) (A for additive) Please set names of lists "Z" and "K"! |
subpopInfo |
The information on group memberships (e.g., subgroups for the population) will be required. You can set a vector of group names (or clustering ids) for each genotype as this argument. This vector should be factor. |
nSubpop |
When 'subpopInfo = NULL', 'subpopInfo' will be automatically determined by using |
nPcsFindCluster |
Number of principal components to be used for 'adegenet::find.clusters'. This argument is used inly when 'subpopInfo' is 'NULL'. |
include.epistasis |
Whether or not including the genome-wide epistastic effects into the model to adjust ZETA. |
package.MM |
The package name to be used when solving mixed-effects model. We only offer the following three packages:
"RAINBOWR", "MM4LMM" and "gaston". Default package is 'gaston'.
See more details at |
A List of
Adjusted ZETA including only one kernel.
A vector of 'subpopInfo' used in this function.
A matrix of covariates used in the mixed effects model.
#'
Results of mixed-effects model for multiple kernels.
'nSubpop' used in this function.
'include.epistasis' used in this function.
Rio S, Mary-Huard T, Moreau L, Bauland C, Palaffre C, et al. (2020) Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering. PLOS Genetics 16(3): e1008241.
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