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sommer (version 1.6)

Solving Mixed Model Equations in R

Description

Mixed model equation solver allowing the specification of variance covariance structures of random effects. ML/REML estimates are obtained using the Average Information, Expectation-Maximization, Newton-Raphson, or Efficient Mixed Model Association algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominant and epistatic relationship structures or other covariance structures in R, but also functional as a regular mixed model program.

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Version

Install

install.packages('sommer')

Monthly Downloads

4,273

Version

1.6

License

GPL-3

Maintainer

Giovanny CovarrubiasPazaran

Last Published

May 19th, 2016

Functions in sommer (1.6)

NR

Newton-Raphson Algorithm
fdr

False Discovery Rate calculation
A.mat

Additive relationship matrix
adiag1

Binds arrays corner-to-corner
big.peaks.col

Peak search by first derivatives
fitted.mmer

fitted form a GLMM fitted with mmer
plot.mmer

plot form a GLMM plot with mmer
CPdata

Genotypic and Phenotypic data for a CP population (F1; cross between 2 highly heterozygote individuals; i.e. humans, fruit crops, bredding populations in recurrent selection).
AI2

Average Information Algorithm
E.mat

Epistatic relationship matrix
h2

Broad sense heritability calculation.
D.mat

Dominance relationship matrix
cornHybrid

Corn crosses and markers
AI3

Average Information Algorithm
hdm

Half Diallel Matrix
Technow_data

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

wheat lines dataset
poe

Short poems from Latin America, and other places why not?
summary.mmer

summary form a GLMM fitted with mmer
AI

Average Information Algorithm
map.plot

Creating a genetic map
anova.mmer

anova form a GLMM fitted with mmer
design.score

design score for the model to be tested
randef

extracting random effects
PolyData

Genotypic and Phenotypic data for a potato polyploid population
FDdata

half diallel data for corn hybrids
HDdata

half diallel data for corn hybrids
PEV

Selecting the best training population for genomic selection
score.calc

Score calculation for markers
bag

Creating a fixed effect matrix with significant GWAS markers
transp

Creating color with transparency
bathy.colors

Generate a sequence of colors for plotting bathymetric data.
brewer.pal

Generate a sequence of colors for groups.
coef.mmer

coef form a GLMM fitted with mmer
EM

Expectation Maximization Algorithm
wheatLines

wheat lines dataset
mmer2

Mixed Model Equations in R 2
EM2

Expectation Maximization Algorithm
jet.colors

Generate a sequence of colors alog the jet colormap.
TP.prep

Selecting the best training population for genomic selection
mmer

Mixed Model Equations in R
EMMA

Efficient Mixed Model Association Algorithm
atcg1234

Letter to number converter
sommer-package

Solving Mixed Model Equations in R
residuals.mmer

Residuals form a GLMM fitted with mmer