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sommer: Solving Mixed Model Equations in R

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects and unknown variance-covariance structures (i.e. heterogeneous and unstructured variance models) (Covarrubias-Pazaran, 2016; Maier et al., 2015). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms. Designed for genomic prediction and genome wide association studies (GWAS), particularly focused in the p > n problem (more coefficients than observations) and dense known covariance structures for levels of random effects. Spatial models can also be fitted using i.e. the two-dimensional spline functionality available in sommer.

Installation

You can install the development version of sommer from GitHub:

devtools::install_github('covaruber/sommer')

Vignettes

Development

The sommer package is under active development. If you are an expert in mixed models, statistics or programming and you know how to implement of the following:

the minimum degree ordering algorithm
the symbolic cholesky factorization
factor analytic structure
generalized linear models

please help us to take sommer to the next level. Drop me an email or push some changes through github :)

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Version

Install

install.packages('sommer')

Monthly Downloads

5,517

Version

4.3.3

License

GPL (>= 2)

Maintainer

Giovanny Covarrubias-Pazaran

Last Published

November 13th, 2023

Functions in sommer (4.3.3)

Rice lines dataset

Genotypic and Phenotypic data from single cross hybrids (Technow et al.,2014)

Reaction times in a sleep deprivation study

Gryphon data from the Journal of Animal Ecology

anova form a GLMM fitted with mmec

Letter to number converter

Expectation Maximization Algorithm

atc covariance structure

Combined relationship matrix H

data frame to matrix

Function for creating B-spline basis functions (Eilers & Marx, 2010)

Generate a sequence of colors for plotting bathymetric data.

add.diallel.vars

add.diallel.vars

Calculation of linkage disequilibrium decay

Genome wide association study analysis

Multivariate Efficient Mixed Model Association Algorithm

atr covariance structure

Binds arrays corner-to-corner

anova form a GLMM fitted with mmer

Imputing a matrix using correlations

Epistatic relationship matrix

Yield of oats in a split-block experiment

diagonal covariance structure

diagonal covariance structure

coef form a GLMM fitted with mmec

customized covariance structure

customized covariance structure

wheat lines dataset

fixed effect constraint indication matrix

fitted form a LMM fitted with mmer

fitted form a LMM fitted with mmec

identity covariance structure

covariance between random effects

Imputing a numeric or character vector

plot the change of VC across iterations

coef form a GLMM fitted with mmer

plot form a LMM plot with mmec

general variance structure specification

mixed model equations for c coefficients

fixed indication matrix

mixed model equations for r records

Creating a genetic map plot

Creating a manhattan plot

Create a GE correlation matrix for simulation purposes.

Predict form of a LMM fitted with mmer

reduced rank covariance structure

Effective population size based on marker matrix

extracting random effects

bivariateRun functionality

Legendre polynomial matrix

Residuals form a GLMM fitted with mmer

Reduced Model Matrix

Generate a sequence of colors alog the jet colormap.

Build a hybrid marker matrix using parental genotypes from inbred individuals

Residuals form a GLMM fitted with mmec

Decreasing logarithmic trend

Get Tensor Product Spline Mixed Model Incidence Matrices

list or vector to unstructured matrix

Predict form of a LMM fitted with mmec

Solving Mixed Model Equations in R
Figure: mai.png

Figure: mai.png

plot form a LMM plot with mmer

Get Tensor Product Spline Mixed Model Incidence Matrices

Two-dimensional penalised tensor-product of marginal B-Spline basis.

Two-dimensional penalised tensor-product of marginal B-Spline basis.

summary form a GLMM fitted with mmec

summary form a GLMM fitted with mmer

Stacking traits in a dataset

variance structure specification

vpredict form of a LMM fitted with mmer

Two-dimensional penalised tensor-product of marginal B-Spline basis.

unstructured covariance structure

Wald Test for Model Coefficients

unstructured covariance structure

unstructured indication matrix

Creating color with transparency

transformConstraints

transformConstraints

variance structure specification

variance structure specification

Autocorrelation matrix of order 1.

Additive relationship matrix

Blue Tit Data for a Quantitative Genetic Experiment

Dominance relationship matrix

Average Information Algorithm

Autocorrelation Moving average.

Compound symmetry matrix

Broad sense heritability calculation.

Data to fit indirect genetic effects.

DT_augment design example.

Genotypic and Phenotypic data for a potato polyploid population

Data for different experimental designs

Genotypic and Phenotypic data for a CP population

Simulated data for random regression

Corn crosses and markers

Full diallel data for corn hybrids

Broad sense heritability calculation.

half diallel data for corn hybrids

Full diallel data for corn hybrids