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sommer (version 3.1)

Solving Mixed Model Equations in R

Description

Structural multivariate-univariate linear mixed model solver for multiple random effects allowing the specification of variance-covariance structures for random effects and allowing the fit of heterogeneous variance models (Maier et al., 2015 ; Covarrubias-Pazaran, 2016 ). ML/REML estimates can be obtained using the Direct-Inversion Newton-Raphson, and Efficient Mixed Model Association algorithms. Designed for genomic prediction and genome wide association studies (GWAS), particularly focused in the p > n problem (more coefficients than observations) to include multiple relationship matrices or other covariance structures.

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Version

Install

install.packages('sommer')

Monthly Downloads

7,425

Version

3.1

License

GPL-3

Maintainer

Giovanny Covarrubias-Pazaran

Last Published

October 29th, 2017

Functions in sommer (3.1)

Blue Tit Data for a Quantitative Genetic Experiment

Genotypic and Phenotypic data for a CP population

half diallel data for corn hybrids

Multivariate Efficient Mixed Model Association Algorithm

Applying postblocking in a field

Applying linear postblocking in a field

design score for the model to be tested

eigen decomposition functionality

is.square.matrix

Test for square matrix

Generate a sequence of colors alog the jet colormap.

All typical colors in R easy to access.

Nearest neighbour adjustment

plot form a LMM plot with mmer

extracting random effects

wheat lines dataset

Yield of oats in a split-block experiment

Genotypes from an F1(CP) cross to show phasing

Full diallel data for corn hybrids

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

Rice lines dataset

Letter to number converter

augment design example.

False Discovery Rate calculation

Filling the design of an experiment

Broad sense heritability calculation.

Hadamard product of two matrices

The trace of a matrix

Peak search by first derivatives

Phasing F1 (CP) data in biparental populations

pin functionality

Expectation Maximization Algorithm

Data for different experimental designs

Binds arrays corner-to-corner

and functionality

anova form a GLMM fitted with mmer

at functionality

Applying transversal postblocking in a field

Generate a sequence of colors for groups.

fitted form a GLMM fitted with mmer

g functionality

Half Diallel Matrix

grouping functionality

Gryphon data from the Journal of Animal Ecology

Dominance relationship matrix

Epistatic relationship matrix

Generate a sequence of colors for plotting bathymetric data.

Creating a fixed effect matrix with significant GWAS markers

mixed model equations in R

residuals.MMERM

Residuals form a GLMM fitted with mmer

Score calculation for markers

mixed model equations in R

Additive relationship matrix

Average Information Algorithm

Genome Wide Association Analysis

Genome Wide Association Analysis

coef form a GLMM fitted with mmer

Corn crosses and markers

Imputing a numeric or character vector

is.diagonal.matrix

Test for diagonal square matrix

Pedigree to matrix

Solving Mixed Model Equations in R Figure: mai.png

Figure: mai.png

summary form a GLMM fitted with mmer

vctable functionality

Peak search by first derivatives

vctable.help functionality

Creating a manhattan plot

Creating a genetic map plot

Multivariate Newton-Raphson Algorithm

Genotypic and Phenotypic data for a potato polyploid population

Broad sense heritability calculation.

False Discovery Rate calculation

Creating color with transparency

us functionality