Learn R Programming

⚠️There's a newer version (4.4.1) of this package.Take me there.

sommer: Solving Mixed Model Equations in R

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016; Maier et al., 2015; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.

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 :)

Copy Link

Version

Install

install.packages('sommer')

Monthly Downloads

4,275

Version

4.3.4

License

GPL (>= 2)

Maintainer

Giovanny Covarrubias-Pazaran

Last Published

March 17th, 2024

Functions in sommer (4.3.4)

Broad sense heritability calculation.

Blue Tit Data for a Quantitative Genetic Experiment

half diallel data for corn hybrids

Data to fit indirect genetic effects.

Full diallel data for corn hybrids

Multivariate Efficient Mixed Model Association Algorithm

Expectation Maximization Algorithm

Genotypic and Phenotypic data for a potato polyploid population

Yield of oats in a split-block experiment

Epistatic relationship matrix

Reaction times in a sleep deprivation study

Rice lines dataset

Binds arrays corner-to-corner

anova form a GLMM fitted with mmec

Simulated data for random regression

atc covariance structure

anova form a GLMM fitted with mmer

Genome wide association study analysis

Combined relationship matrix H

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

Build a hybrid marker matrix using parental genotypes from inbred individuals

coef form a GLMM fitted with mmec

wheat lines dataset

Calculation of linkage disequilibrium decay

add.diallel.vars

add.diallel.vars

bivariateRun functionality

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

general variance structure specification

data frame to matrix

customized covariance structure

Imputing a numeric or character vector

identity covariance structure

Generate a sequence of colors alog the jet colormap.

Decreasing logarithmic trend

Creating a manhattan plot

Creating a genetic map plot

fixed effect constraint indication matrix

mixed model equations for c coefficients

plot the change of VC across iterations

fitted form a LMM fitted with mmec

diagonal covariance structure

plot form a LMM plot with mmec

Predict form of a LMM fitted with mmec

diagonal covariance structure

Residuals form a GLMM fitted with mmec

Residuals form a GLMM fitted with mmer

Predict form of a LMM fitted with mmer

atr covariance structure

Generate a sequence of colors for plotting bathymetric data.

coef form a GLMM fitted with mmer

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

Solving Mixed Model Equations in R
Figure: mai.png

Figure: mai.png

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

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

plot form a LMM plot with mmer

Imputing a matrix using correlations

fixed indication matrix

Letter to number converter

fitted form a LMM fitted with mmer

mixed model equations for r records

Create a GE correlation matrix for simulation purposes.

reduced rank covariance structure

Effective population size based on marker matrix

Proportion of missing data

variance structure specification

variance structure specification

atcg1234BackTransform

Letter to number converter

unstructured covariance structure

unstructured covariance structure

covariance between random effects

Wald Test for Model Coefficients

Legendre polynomial matrix

customized covariance structure

list or vector to unstructured matrix

extracting random effects

Reduced Model Matrix

Stacking traits in a dataset

transformConstraints

transformConstraints

Get Tensor Product Spline Mixed Model Incidence Matrices

Get Tensor Product Spline Mixed Model Incidence Matrices

Creating color with transparency

unstructured indication matrix

summary form a GLMM fitted with mmec

summary form a GLMM fitted with mmer

variance structure specification

vpredict form of a LMM fitted with mmer

DT_augment design example.

Additive relationship matrix

Autocorrelation matrix of order 1.

Average Information Algorithm

Autocorrelation Moving average.

Compound symmetry matrix

Dominance relationship matrix

Genotypic and Phenotypic data for a CP population

Corn crosses and markers

Broad sense heritability calculation.

Gryphon data from the Journal of Animal Ecology

Full diallel data for corn hybrids

Data for different experimental designs