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

• Quick start for the sommer package
• Moving to newer versions of sommer
• Quantitative genetics using the sommer package
• GxE models in sommer
• lme4 vs sommer

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 :)