Multivariate mixed model solver for multiple random effects allowing the specification of variance covariance structures. ML/REML estimates are obtained using the Average Information (AI), Expectation-Maximization (EM), Newton-Raphson (NR), or Efficient Mixed Model Association (EMMA) algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominance and epistatic relationship structures or other covariance structures in R, but also functional as a regular mixed model program. Multivariate models (multiple responses) can be fitted currently with NR, AI and EMMA algorithms allowing multiple random effects as well. Covariance structures for the residual component is currently supported only for balanced univariate Newton Raphson models.
|Date of publication||2017-01-03 06:19:01|
|Maintainer||Giovanny Covarrubias-Pazaran <email@example.com>|
adiag1: Binds arrays corner-to-corner
AI: Average Information Algorithm
ai2help: Average Information Algorithm
A.mat: Additive relationship matrix
anova.mmer: anova form a GLMM fitted with mmer
anova.mmerM: anova form a GLMM fitted with mmer
anova.MMERM1: anova form a GLMM fitted with mmer
AR1.mat: Autocorrelation matrix of order 1.
ARMA.mat: Autorregressive moving average matrix
atcg1234: Letter to number converter
augment: augment design example.
bathy.colors: Generate a sequence of colors for plotting bathymetric data.
big.peaks.col: Peak search by first derivatives
brewer.pal: Generate a sequence of colors for groups.
coef.mmer: coef form a GLMM fitted with mmer
coef.mmerM: coef form a GLMM fitted with mmer
coef.MMERM1: coef form a GLMM fitted with mmer
cornHybrid: Corn crosses and markers
CPdata: Genotypic and Phenotypic data for a CP population
CS.mat: Compound symmetry matrix
design.score: design score for the model to be tested
D.mat: Dominance relationship matrix
eigenGWAS: Unraveling selection signatures with eigenGWAS
EM: Expectation Maximization Algorithm
EM2: Expectation Maximization Algorithm
E.mat: Epistatic relationship matrix
EMMA: Efficient Mixed Model Association Algorithm
ExpDesigns: Data for different experimental designs
F1geno: Genotypes from an F1(CP) cross to show phasing
FDdata: Full diallel data for corn hybrids
fdr: False Discovery Rate calculation
fdr2: False Discovery Rate calculation
fitted.mmer: fitted form a GLMM fitted with mmer
fitted.mmerM: fitted form a GLMM fitted with mmer
fitted.MMERM1: fitted form a GLMM fitted with mmer
gryphondata: Gryphon data from the Journal of Animal Ecology
h2: Broad sense heritability calculation.
hadamard.prod: Hadamard product of two matrices
HDdata: half diallel data for corn hybrids
hdm: Half Diallel Matrix
hits: Creating a fixed effect matrix with significant GWAS markers
impute: Imputing a numeric or character vector
is.diagonal.matrix: Test for diagonal square matrix
is.square.matrix: Test for square matrix
jet.colors: Generate a sequence of colors alog the jet colormap.
LD.decay: Calculation of linkage disequilibrium decay
MAI: Multivariate Average Information Algorithm
MAI2: Multivariate Average Information Algorithm
manhattan: Creating a manhattan plot
map.plot: Creating a genetic map plot
matrix.trace: The trace of a matrix
maxi.qtl: Peak search by first derivatives
MEMMA: Multivariate Efficient Mixed Model Association Algorithm
mmer: Mixed Model Equations in R
mmer2: Mixed Model Equations in R v2
MMERM: Multivariate mixed model solver to be called inside mmer
mmerSNOW: Mixed Model Equations in R univariate
MNR: Multivariate Newton-Raphson Algorithm
my.colors: All typical colors in R easy to access.
name.change: renaming a vector by adding zeros
nna: Nearest neighbour adjustment
NR: Newton-Raphson Algorithm
NR22: Newton-Raphson Algorithm
NRR: Newton-Raphson Algorithm including Residual structures
PEV: Selecting the best training population for genomic selection
phase.F1: Phasing F1 (CP) data in biparental populations
plot.mmer: plot form a GLMM plot with mmer
plot.mmerM: plot form a GLMM plot with mmer
plot.MMERM1: plot form a GLMM plot with mmer
poe: Short poems from Latin America, and other places why not?
PolyData: Genotypic and Phenotypic data for a potato polyploid...
randef: extracting random effects
residuals.mmer: Residuals form a GLMM fitted with mmer
residuals.mmerM: Residuals form a GLMM fitted with mmer
residuals.MMERM1: Residuals form a GLMM fitted with mmer
RICE: Rice lines dataset
score.calc: Score calculation for markers
score.calcMV: Score calculation for markers
sommer-package: Solving Mixed Model Equations in R
summary.mmer: summary form a GLMM fitted with mmer
summary.mmerM: summary form a GLMM fitted with mmer
summary.MMERM1: summary form a GLMM fitted with mmer
Technow_data: Genotypic and Phenotypic data from single cross hybrids...
TP.prep: Selecting the best training population for genomic selection
transp: Creating color with transparency
wheatLines: wheat lines dataset
yates.oats: Yield of oats in a split-block experiment