Package: sommer 4.3.6

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 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; 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.

Authors:Giovanny Covarrubias-Pazaran [aut, cre]

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sommer.pdf |sommer.html
sommer/json (API)

# Install 'sommer' in R:
install.packages('sommer', repos = c('https://covaruber.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/covaruber/sommer/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • A_example - Broad sense heritability calculation.
  • A_gryphon - Gryphon data from the Journal of Animal Ecology
  • A_ige - Data to fit indirect genetic effects.
  • DT_augment - DT_augment design example.
  • DT_btdata - Blue Tit Data for a Quantitative Genetic Experiment
  • DT_cornhybrids - Corn crosses and markers
  • DT_cpdata - Genotypic and Phenotypic data for a CP population
  • DT_example - Broad sense heritability calculation.
  • DT_expdesigns - Data for different experimental designs
  • DT_fulldiallel - Full diallel data for corn hybrids
  • DT_gryphon - Gryphon data from the Journal of Animal Ecology
  • DT_h2 - Broad sense heritability calculation.
  • DT_halfdiallel - Half diallel data for corn hybrids
  • DT_ige - Data to fit indirect genetic effects.
  • DT_legendre - Simulated data for random regression
  • DT_mohring - Full diallel data for corn hybrids
  • DT_polyploid - Genotypic and Phenotypic data for a potato polyploid population
  • DT_rice - Rice lines dataset
  • DT_sleepstudy - Reaction times in a sleep deprivation study
  • DT_technow - Genotypic and Phenotypic data from single cross hybrids
  • DT_wheat - Wheat lines dataset
  • DT_yatesoats - Yield of oats in a split-block experiment
  • DTi_cornhybrids - Corn crosses and markers
  • GT_cornhybrids - Corn crosses and markers
  • GT_cpdata - Genotypic and Phenotypic data for a CP population
  • GT_polyploid - Genotypic and Phenotypic data for a potato polyploid population
  • GT_rice - Rice lines dataset
  • GT_wheat - Wheat lines dataset
  • GTn_rice - Rice lines dataset
  • MP_cpdata - Genotypic and Phenotypic data for a CP population
  • MP_polyploid - Genotypic and Phenotypic data for a potato polyploid population
  • Md_technow - Genotypic and Phenotypic data from single cross hybrids
  • Mf_technow - Genotypic and Phenotypic data from single cross hybrids
  • P_gryphon - Gryphon data from the Journal of Animal Ecology

On CRAN:

average-informationmixed-modelsrcpparmadillo

12.29 score 38 stars 9 packages 260 scripts 5.0k downloads 39 mentions 83 exports 7 dependencies

Last updated 5 days agofrom:5030182a8f. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-win-x86_64WARNINGNov 11 2024
R-4.5-linux-x86_64WARNINGNov 11 2024
R-4.4-win-x86_64WARNINGNov 11 2024
R-4.4-mac-x86_64WARNINGNov 11 2024
R-4.4-mac-aarch64WARNINGNov 11 2024
R-4.3-win-x86_64WARNINGNov 11 2024
R-4.3-mac-x86_64WARNINGNov 11 2024
R-4.3-mac-aarch64WARNINGNov 11 2024

Exports:A.matadd.diallel.varsadiag1AIanova.mmecanova.mmerAR1ARMAatcatcg1234atcg1234BackTransformatrbathy.colorsbbasisbivariateRunbuild.HMMcoef.mmeccoef.mmercorImputationcovcCScsccsrD.matdfToMatrixdscdsrE.matEMfcmfitted.mmecfitted.mmerfixmgvsrGWASH.matimputeviscjet.colorsLD.decayleglist2usmatlogspacemanhattanmap.plotMEMMAmmecmmerneMarkeroverlayplot.mmecplot.mmerpmonitorpredict.mmecpredict.mmerpropMissingr2randefredmmresiduals.mmecresiduals.mmerrrcsimGECorMatspl2Daspl2Dbspl2Dcspl2DmatsstackTraitsummary.mmecsummary.mmertpstpsmmbwrappertransformConstraintstranspunsmuscusrvpredictvpredict.mmervsvscvsrwald.test

Dependencies:crayonlatticeMASSMatrixRcppRcppArmadilloRcppProgress

Fitting genotype by environment models in sommer

Rendered fromv4.sommer.gxe.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-07-31
Started: 2020-06-25

Changes and FAQs for the sommer package

Rendered fromv2.sommer.changes.and.faqs.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-07-31
Started: 2020-06-25

Quantitative genetics using the sommer package

Rendered fromv3.sommer.qg.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-07-31
Started: 2020-06-25

Quick start for the sommer package

Rendered fromv1.sommer.quick.start.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-03-23
Started: 2020-06-25

Spatial modeling using the sommer package

Rendered fromv6.sommer.spatial.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2023-06-01
Started: 2021-10-08

Translating lme4 models to sommer

Rendered fromv5.sommer.vs.lme4.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-05-13
Started: 2021-01-26

Readme and manuals

Help Manual

Help pageTopics
*So*lving *M*ixed *M*odel *E*quations in *R*sommer
Additive relationship matrixA.mat
add.diallel.varsadd.diallel.vars
Binds arrays corner-to-corneradiag1
Average Information AlgorithmAI
anova form a GLMM fitted with mmecanova.mmec
anova form a GLMM fitted with mmeranova.mmer
Autocorrelation matrix of order 1.AR1
Autocorrelation Moving average.ARMA
atc covariance structureatc
Letter to number converteratcg1234
Letter to number converteratcg1234BackTransform
atr covariance structureatr
Generate a sequence of colors for plotting bathymetric data.bathy.colors
Function for creating B-spline basis functions (Eilers & Marx, 2010)bbasis
bivariateRun functionalitybivariateRun
Build a hybrid marker matrix using parental genotypes from inbred individualsbuild.HMM
coef form a GLMM fitted with mmeccoef.mmec
coef form a GLMM fitted with mmercoef.mmer
Imputing a matrix using correlationscorImputation
covariance between random effectscovc
Compound symmetry matrixCS
customized covariance structurecsc
customized covariance structurecsr
Dominance relationship matrixD.mat
data frame to matrixdfToMatrix
diagonal covariance structuredsc
diagonal covariance structuredsr
DT_augment design example.DT_augment
Blue Tit Data for a Quantitative Genetic ExperimentDT_btdata
Corn crosses and markersDTi_cornhybrids DT_cornhybrids GT_cornhybrids
Genotypic and Phenotypic data for a CP populationDT_cpdata GT_cpdata MP_cpdata
Broad sense heritability calculation.A_example DT_example
Data for different experimental designsDT_expdesigns
Full diallel data for corn hybridsDT_fulldiallel
Gryphon data from the Journal of Animal EcologyA_gryphon DT_gryphon P_gryphon
Broad sense heritability calculation.DT_h2
half diallel data for corn hybridsDT_halfdiallel
Data to fit indirect genetic effects.A_ige DT_ige
Simulated data for random regressionDT_legendre
Full diallel data for corn hybridsDT_mohring
Genotypic and Phenotypic data for a potato polyploid populationDT_polyploid GT_polyploid MP_polyploid
Rice lines datasetDT_rice GTn_rice GT_rice
Reaction times in a sleep deprivation studyDT_sleepstudy
Genotypic and Phenotypic data from single cross hybrids (Technow et al.,2014)Ad_technow Af_technow DT_technow Md_technow Mf_technow
wheat lines datasetDT_wheat GT_wheat
Yield of oats in a split-block experimentDT_yatesoats
Epistatic relationship matrixE.mat
Expectation Maximization AlgorithmEM
fixed effect constraint indication matrixfcm
fitted form a LMM fitted with mmecfitted.mmec
fitted form a LMM fitted with mmerfitted.mmer
fixed indication matrixfixm
general variance structure specificationgvsr
Genome wide association study analysisGWAS
Two-way id by features tableH
Combined relationship matrix HH.mat
Imputing a numeric or character vectorimputev
identity covariance structureisc
Generate a sequence of colors alog the jet colormap.jet.colors
Calculation of linkage disequilibrium decayLD.decay
Legendre polynomial matrixleg
list or vector to unstructured matrixlist2usmat
Decreasing logarithmic trendlogspace
Creating a manhattan plotmanhattan
Creating a genetic map plotmap.plot
Multivariate Efficient Mixed Model Association AlgorithmMEMMA
*m*ixed *m*odel *e*quations for *c* coefficientsmmec
*m*ixed *m*odel *e*quations for *r* recordsmmer
Effective population size based on marker matrixneMarker
Overlay Matrixoverlay
plot form a LMM plot with mmecplot.mmec
plot form a LMM plot with mmerplot.mmer
plot the change of VC across iterationspmonitor
Predict form of a LMM fitted with mmecpredict.mmec
Predict form of a LMM fitted with mmerpredict.mmer
Proportion of missing datapropMissing
Reliabilityr2
extracting random effectsrandef
Reduced Model Matrixredmm
Residuals form a GLMM fitted with mmecresiduals.mmec
Residuals form a GLMM fitted with mmerresiduals.mmer
reduced rank covariance structurerrc
Create a GE correlation matrix for simulation purposes.simGECorMat
Two-dimensional penalised tensor-product of marginal B-Spline basis.spl2Da
Two-dimensional penalised tensor-product of marginal B-Spline basis.spl2Db
Two-dimensional penalised tensor-product of marginal B-Spline basis.spl2Dc
Get Tensor Product Spline Mixed Model Incidence Matricesspl2Dmats
Stacking traits in a datasetstackTrait
summary form a GLMM fitted with mmecprint.mmec print.summary.mmec summary.mmec
summary form a GLMM fitted with mmerprint.mmer print.summary.mmer summary.mmer
Get Tensor Product Spline Mixed Model Incidence Matricestps
Get Tensor Product Spline Mixed Model Incidence Matricestpsmmbwrapper
transformConstraintstransformConstraints
Creating color with transparencytransp
unstructured indication matrixunsm
unstructured covariance structureusc
unstructured covariance structureusr
vpredict form of a LMM fitted with mmervpredict vpredict.mmer
variance structure specificationvs
variance structure specificationvsc
variance structure specificationvsr
Wald Test for Model Coefficientsprint.wald.test wald.test