1) Single environment model | 2) MET: main effect model | 3) MET: diagonal model (DG) | 4) MET: compund symmetry model (CS) | 5) MET: unstructured model (US) | 6) MET: random regression model | 7) Other GxE covariance structures | 8) Finlay-Wilkinson regression | 9) Factor analytic (reduced rank) model | 10) Two stage analysis | Literature
Package: sommer 4.4.5
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:
sommer_4.4.5.tar.gz
sommer_4.4.5.zip(r-4.7)sommer_4.4.5.zip(r-4.6)sommer_4.4.5.zip(r-4.5)
sommer_4.4.5.tgz(r-4.6-x86_64)sommer_4.4.5.tgz(r-4.6-arm64)sommer_4.4.5.tgz(r-4.5-x86_64)sommer_4.4.5.tgz(r-4.5-arm64)
sommer_4.4.5.tar.gz(r-4.7-arm64)sommer_4.4.5.tar.gz(r-4.7-x86_64)sommer_4.4.5.tar.gz(r-4.6-arm64)sommer_4.4.5.tar.gz(r-4.6-x86_64)
sommer_4.4.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sommer/json (API)
| # Install 'sommer' in R: |
| install.packages('sommer', repos = c('https://covaruber.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/covaruber/sommer/issues
Uses libs:
average-informationmixed-modelsrcpparmadilloopenblascppopenmp
Last updated from:23d5230c28. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 194 | ||
| linux-devel-x86_64 | OK | 159 | ||
| source / vignettes | OK | 299 | ||
| linux-release-arm64 | OK | 169 | ||
| linux-release-x86_64 | OK | 174 | ||
| macos-release-arm64 | OK | 193 | ||
| macos-release-x86_64 | OK | 301 | ||
| macos-oldrel-arm64 | OK | 217 | ||
| macos-oldrel-x86_64 | OK | 420 | ||
| windows-devel | OK | 173 | ||
| windows-release | OK | 189 | ||
| windows-oldrel | OK | 165 | ||
| wasm-release | OK | 120 |
Exports:A.matanova.mmesAR1ARMAatmatrcoef.mmescorImputationcovmCScsmcsrD.matdfToMatrixdsmdsrE.matfitted.mmesfixmGWASH.matismmmermmesMNRplot.mmespmonitorpredict.mmesr2randefresiduals.mmesspl2Dcspl2Dmatssummary.mmestpsmmbwrapperunsmunsm2usmusrvpredictvsvsmvsr
Dependencies:crayonenhancerlatticeMASSMatrixRcppRcppArmadilloRcppProgress
Fitting genotype by environment models in sommer
Last update: 2025-11-18
Started: 2025-04-01
Quantitative genetics using the sommer package
SECTION 1: Introduction | Backgrounds in linear algebra | SECTION 2: Topics in quantitative genetics | 1) Marker and non-marker based heritability calculation | 2) Specifying heterogeneous variances in univariate models | 3) Using the vpredict calculator | 3.1) Standar error for heritability | 4) Half and full diallel designs (use of the overlay) | 5) Genomic selection: predicting mendelian sampling | 6) Indirect genetic effects | 7) Genomic selection: single cross prediction | 8) Multivariate genetic models and genetic correlations | SECTION 3: Special topics in Quantitative genetics | 1) Partitioned model | 2) UDU' decomposition | 3) Mating designs | North Carolina Design I (Nested design) | North Carolina Design II (Factorial design) | 4) GWAS by GBLUP | Final remarks | Literature
Last update: 2025-11-18
Started: 2025-04-01
Spatial modeling using the sommer package
SECTION 1: Introduction | Backgrounds in tensor products | SECTION 2: Spatial models | 1) Two dimensional splines (multiple spatial components) | 2) Two dimensional splines in single field (single spatial component) | 3) Spatial models in multiple trials at once | Literature
Last update: 2025-11-18
Started: 2025-04-01
Translating lme4 models to sommer
1) Random slopes | 2) Random slopes and random intercepts (without correlation) | 3) Random slopes and random intercepts (with correlation) | 4) Random slopes with a different intercept | 4) Other models available in sommer but not in lme4 | Literature
Last update: 2025-11-18
Started: 2025-04-01
