Package: plantmix 1.0.4

plantmix: Genetic Study of Plant Mixtures

Fit linear mixed models dedicated to the genetic study of plant mixtures, such as those based on general and specific mixing abilities (GMA-SMA) as well as direct and social breeding values (DBV-SBV), also known as direct and indirect genetic effects (DGE-IGE). More details in Forst et al (2019, <doi:10.1016/j.fcr.2019.107571>) for GMA-SMA models, and Salomon et al (2026, <doi:10.1093/genetics/iyag177>) for DBV-SBV models. The package also provides functions to optimize experimental designs, simulate data sets and compute interaction indices.

Authors:Timothee Flutre [aut, ctb, cre], INRAE [cph, fnd], Jerome Enjalbert [ctb], Emma Forst [ctb], Maxence Remerand [ctb], Jemay Salomon [ctb]

plantmix_1.0.4.tar.gz
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plantmix_1.0.4.tar.gz(r-4.7-arm64)plantmix_1.0.4.tar.gz(r-4.7-x86_64)plantmix_1.0.4.tar.gz(r-4.6-arm64)plantmix_1.0.4.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
plantmix/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.65 score 335 downloads 39 exports 34 dependencies

Last updated from:7e75ce63c7. Checks:14 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK273
linux-devel-x86_64OK271
source / vignettesOK552
linux-release-arm64OK250
linux-release-x86_64OK226
macos-release-arm64OK353
macos-release-x86_64OK486
macos-oldrel-arm64OK343
macos-oldrel-x86_64OK719
windows-devel-arm64OK500
windows-devel-x86_64OK280
windows-release-arm64OK500
windows-release-x86_64OK299
windows-oldrel-x86_64OK323
wasm-releaseFAIL150

Exports:CCestimGRMestimRYMRepestimRYRepfitDBVSBVinterfitGMASMAgetDesignBinaryCropMixgetDesignBinaryVarMixgetMixtureListgetMixturesPerGenoimageMatinfoCriterioninvvecinvvecMixesLERmixSowingWeightmkAllZSMAmkZGMAmkZinterspemkZSMAnbSeedsToSownInPurenormBiasErrorparamBoot4TMBpivotMixData2LongpivotMixData2WideplotDesignCropMixplotDesignVarMixplotDiallelRIIRIInetrmatnormRYRYMRYPRYTsimulDBVSBVintersimulGenosDoseStructsummarizeGMASMAsvec

Dependencies:bootclicpp11farverggplot2gluegtableigraphisobandlabelinglatticelifecyclelme4magrittrMASSMatrixminqanlmenloptrpkgconfigR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangS7scalesTMBvctrsviridisLitewithr

Example of DBV-SBV models for species mixtures in a tester-based design
Preamble | Simulate data | Simulate the genotypes | Set the dimensions | SNP genotypes | Additive genetic relationships | Simulate the phenotypes | Design sparsity | Indices of plant mixtures | RYT (LER) and RYP | RYM | Explore the data | Yield map | Infer the parameters | Using intercrops only | Prepare the inputs | Fit the model | Checks | Parametric bootstrap | Using both sole crops and intercrops | Reference | Appendix
Rendered fromvig3_DBV-SBV_crop-mix_testers.Rmdusingknitr::rmarkdown

Last update: 2026-10-14
Started: 2026-06-09

Introduction to GMA-SMA models
Preamble | Models | Overview | Notations | Major assumptions | Model 1 | Model 2 | Model 3 | Models in vector form | Other models | Examples of design matrices | Design matrix for GMAs | Design matrix for SMAs | Model 2' | Model 2'' | Model 3' | Data simulation | Sparse design | Design matrices | Parameters | Phenotypes | Inference | Model fits | Checks | Model comparisons | Reference | Appendix
Rendered fromvig1_intro-GMA-SMA.Rmdusingknitr::rmarkdown

Last update: 2026-06-09
Started: 2026-06-09

Example of GMA-SMA models for varietal mixtures in microplots
Preamble | Overview | Simulate data | Simulate the genotypes | Set the dimensions | SNP genotypes | Additive genetic relationships | Simulate the phenotypes | Incomplete, yet balanced design | Field trial | Design matrices | Parameters | Phenotypes | Infer the parameters | Model 1 | Fit | Check | Model 2 | Model 3 | Model 2' | Model 2'' | Model 3' | Appendix
Rendered fromvig2_GMA-SMA_simul-infer.Rmdusingknitr::rmarkdown

Last update: 2026-06-09
Started: 2026-06-09

Readme and manuals

Help Manual

Help pageTopics
Change in contributionCC
Estimate a GRMestimGRM
RYM with "rep" effectestimRYMRep
RY with "rep" effectestimRYRep
Fit DBV-SBV models for interspecific mixturesfitDBVSBVinter
Fit GMA-SMA modelsfitGMASMA
Optimize design for binary crop mixturesgetDesignBinaryCropMix
Optimize design for binary varietal mixturesgetDesignBinaryVarMix
Reformat composition of mixtures into a listgetMixtureList
Get mixture(s) per genotypegetMixturesPerGeno
Image of a matriximageMat
Information criterioninfoCriterion
Inverse vec operatorinvvec
Inverse vec for mixturesinvvecMixes
Land equivalent ratio (LER)LER
SowingmixSowingWeight
Design matrices of SMAs for GMA-SMA modelsmkAllZSMA
Design matrix of GMAs for GMA-SMA modelsmkZGMA
Design matrices for DBV-SBV models in an inter-specific trialmkZinterspe
Design matrix of SMAs for GMA-SMA modelsmkZSMA
SowingnbSeedsToSownInPure
Normalized bias errornormBiasError
Parametric bootstrap with TMBparamBoot4TMB
Pivot mixture data into the long formatpivotMixData2Long
Pivot mixture data into the wide formatpivotMixData2Wide
Plot design for crop mixturesplotDesignCropMix
Plot design for varietal mixturesplotDesignVarMix
Plot diallelplotDiallel
Relative interaction index (RII)RII
Net Relative interaction index (RIInet)RIInet
Matrix-variate Normal distributionrmatnorm
Relative yield (RY)RY
Relative yield of mixture (RYM)RYM
Relative yield per plant (RYP)RYP
Relative yield total (RYT)RYT
Simulate w.r.t. a DBV-SBV model for interspecific mixturessimulDBVSBVinter
Simulate SNP genotypessimulGenosDoseStruct
Model summarysummarizeGMASMAs
Vec operatorvec