sommer: Solving Mixed Model Equations in R

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.

AuthorGiovanny Covarrubias-Pazaran
Date of publication2017-01-03 06:19:01
MaintainerGiovanny Covarrubias-Pazaran <>

View on CRAN

Man pages

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 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

Files in this package

sommer/R/MMERM.R sommer/R/fdr2.R sommer/R/design.score.R sommer/R/D.mat.R sommer/R/mmer.R sommer/R/MAIhelp.R sommer/R/poe.R sommer/R/score.calcMV.R sommer/R/maxi.qtl.R sommer/R/impute.R sommer/R/hits.R sommer/R/MNR.R sommer/R/TP.prep.R sommer/R/A.mat.R sommer/R/adiag.R sommer/R/MEMMA.R sommer/R/jet.colors.R sommer/R/EM.R sommer/R/ai2help.R sommer/R/NR22.R sommer/R/Rstructures.R sommer/R/PEV.R sommer/R/map.plot.R sommer/R/NR.R sommer/R/hdm.R sommer/R/NRR.R sommer/R/mmerSNOW.R sommer/R/fdr.R sommer/R/big.peaks.col.R sommer/R/EM2.R sommer/R/transp.R sommer/R/phase.F1.R sommer/R/manhattan.R sommer/R/matrix.calculations.R sommer/R/mmer2.R sommer/R/E.mat.R sommer/R/brewer.pal.R sommer/R/score.calc.R sommer/R/LD.decay.R sommer/R/EMMA.R sommer/R/AI.R sommer/R/name.change.R sommer/R/atcg1234.R sommer/R/eigenGWAS.R sommer/R/MAI.R sommer/R/MAI2.R sommer/R/nna.R
sommer/man/anova.MMERM1.Rd sommer/man/MAI.Rd sommer/man/RICE.Rd sommer/man/nna.Rd sommer/man/PEV.Rd sommer/man/EMMA.Rd sommer/man/MAI2.Rd sommer/man/cornHybrid.Rd sommer/man/fitted.mmer.Rd sommer/man/h2.Rd sommer/man/mmerSNOW.Rd sommer/man/mmer.Rd sommer/man/eigenGWAS.Rd sommer/man/residuals.mmerM.Rd sommer/man/EM.Rd sommer/man/MEMMA.Rd sommer/man/residuals.mmer.Rd sommer/man/MNR.Rd sommer/man/Technow_data.Rd sommer/man/AI.Rd sommer/man/plot.mmerM.Rd sommer/man/MMERM.Rd sommer/man/ARMA.mat.Rd sommer/man/fitted.MMERM1.Rd sommer/man/poe.Rd sommer/man/ sommer/man/summary.MMERM1.Rd sommer/man/phase.F1.Rd sommer/man/fdr2.Rd sommer/man/gryphondata.Rd sommer/man/fitted.mmerM.Rd sommer/man/plot.mmer.Rd sommer/man/anova.mmer.Rd sommer/man/AR1.mat.Rd sommer/man/coef.MMERM1.Rd sommer/man/ai2help.Rd sommer/man/CS.mat.Rd sommer/man/FDdata.Rd sommer/man/coef.mmerM.Rd sommer/man/hdm.Rd sommer/man/summary.mmerM.Rd sommer/man/PolyData.Rd sommer/man/big.peaks.col.Rd sommer/man/NRR.Rd sommer/man/transp.Rd sommer/man/D.mat.Rd sommer/man/is.diagonal.matrix.Rd sommer/man/NR22.Rd sommer/man/adiag1.Rd sommer/man/manhattan.Rd sommer/man/bathy.colors.Rd sommer/man/EM2.Rd sommer/man/F1geno.Rd sommer/man/anova.mmerM.Rd sommer/man/map.plot.Rd sommer/man/coef.mmer.Rd sommer/man/score.calc.Rd sommer/man/augment.Rd sommer/man/summary.mmer.Rd sommer/man/mmer2.Rd sommer/man/TP.prep.Rd sommer/man/my.colors.Rd sommer/man/impute.Rd sommer/man/A.mat.Rd sommer/man/name.change.Rd sommer/man/ExpDesigns.Rd sommer/man/matrix.trace.Rd sommer/man/NR.Rd sommer/man/wheatLines.Rd sommer/man/sommer-package.Rd sommer/man/HDdata.Rd sommer/man/residuals.MMERM1.Rd sommer/man/atcg1234.Rd sommer/man/brewer.pal.Rd sommer/man/jet.colors.Rd sommer/man/is.square.matrix.Rd sommer/man/LD.decay.Rd sommer/man/fdr.Rd sommer/man/hits.Rd sommer/man/design.score.Rd sommer/man/plot.MMERM1.Rd sommer/man/score.calcMV.Rd sommer/man/maxi.qtl.Rd sommer/man/yates.oats.Rd sommer/man/CPdata.Rd sommer/man/randef.Rd sommer/man/E.mat.Rd

Questions? Problems? Suggestions? or email at

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.