Package: FieldSimR 1.4.2

FieldSimR: Simulation of Plot Errors and Phenotypes in Plant Breeding Field Trials

Simulation of plot data in multi-environment field trials with one or more traits. FieldSimR's core functionality generates plot errors that capture spatial trend, random error (noise), and extraneous variation, which are combined at a user-defined ratio. Phenotypes can be generated by combining the plot errors with simulated genetic values that capture genotype-by-environment (GxE) interaction using wrapper functions for the R package `AlphaSimR`.

Authors:Christian Werner [aut, cre], Daniel Tolhurst [aut], Jon Bancic [ctb]

FieldSimR_1.4.2.tar.gz
FieldSimR_1.4.2.zip(r-4.7-any)FieldSimR_1.4.2.zip(r-4.6-any)FieldSimR_1.4.2.zip(r-4.5-any)
FieldSimR_1.4.2.tgz(r-4.6-any)FieldSimR_1.4.2.tgz(r-4.5-any)
FieldSimR_1.4.2.tar.gz(r-4.7-any)FieldSimR_1.4.2.tar.gz(r-4.6-any)
FieldSimR_1.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
FieldSimR/json (API)

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

Bug tracker:https://github.com/crwerner/fieldsimr/issues

Pkgdown/docs site:https://crwerner.github.io

Datasets:

On CRAN:

Conda:

7.01 score 15 stars 1 packages 75 scripts 409 downloads 21 exports 25 dependencies

Last updated from:5f4dbdea4c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK131
source / vignettesOK204
linux-releaseOK128
macos-releaseOK175
macos-oldrelOK180
windows-develOK110
windows-releaseOK120
windows-oldrelOK87
wasm-releaseOK101

Exports:compsym_asr_inputcompsym_asr_outputfield_trial_errorgroup_cor_matmake_phenotypesmeasure_variancesmulti_asr_inputmulti_asr_outputplot_effectsplot_histplot_matrixqq_plotrand_cor_matrand_diag_matsample_metsample_variogramskew_diag_matstruc_cor_mattheoretical_variogramunstr_asr_inputunstr_asr_output

Dependencies:cliclustercpp11deldirfarverggplot2gluegtableinterpisobandlabelinglatticelifecycleMatrixmbendR6RColorBrewerRcppRcppEigenrlangS7scalesvctrsviridisLitewithr

Simulation of genetic values based on a compound symmetry model for genotype-by-environment (GxE) interaction
Background | Simulation of genetic values | 1. Genetic architecture and simulation parameters of the two traits | Additive genetic parameters | Dominance genetic parameters | Input parameter list | 2. Simulation of a population of genotypes | 3. Generation of a data frame with simulated genetic values
Rendered fromcompound_symmetry_GxE_demo.Rmdusingknitr::rmarkdown

Last update: 2024-04-03
Started: 2023-03-31

Simulation of genetic values based on an unstructured model for genotype-by-environment (GxE) interaction
Background | Simulation of genetic values | 1. Genetic architecture and simulation parameters of the two traits | Additive genetic parameters | Dominance genetic parameters | Genetic correlation structures | Input parameter list | 2. Simulation of a population of genotypes | 3. Generation of a data frame with simulated genetic values
Rendered fromunstructured_GxE_demo.Rmdusingknitr::rmarkdown

Last update: 2024-04-03
Started: 2023-03-31

Simulation of plot errors and phenotypes in a plant breeding field trial
Background | 1. Simulation of plot errors | 1.1 Field trial layout | 1.2 Total error | 1.3 Spatial error | 1.4 Extraneous variation | 1.5 Simulation of plot errors | 2. Simulation of plot-level phenotypes
Rendered fromspatial_variation_demo.Rmdusingknitr::rmarkdown

Last update: 2024-03-16
Started: 2024-03-04

Readme and manuals

Help Manual

Help pageTopics
Simulate genetic values based on a compound symmetry model for GxE interaction - `AlphaSimR` input parameterscompsym_asr_input
Simulate genetic values based on a compound symmetry model for GxE interaction - Simulation with `AlphaSimR`compsym_asr_output
Plot errors - Example data frameerror_df_bivar
Simulate plot errors in plant breeding field trialsfield_trial_error
Simulate a reduced rank correlation matrix with multiple groupsgroup_cor_mat
Genetic values - Example data framegv_df_unstr
Generate phenotypes - Combine genetic values and plot errorsmake_phenotypes
Measure variances from a covariance matrixmeasure_variances
Simulate genetic values based on a multiplicative model for GxE interaction - `AlphaSimR` input parametersmulti_asr_input
Simulate genetic values based on a multiplicative model for GxE interaction - Simulation with `AlphaSimR`multi_asr_output
Graphics for plot effectsplot_effects
Histogram of effects.plot_hist
Graphics for matricesplot_matrix
Q-Q plotqq_plot
Simulate a random correlation matrixrand_cor_mat
Simulate a random diagonal variance matrixrand_diag_mat
Sample environments from a target populationsample_met
Sample variogramsample_variogram
Simulate a skewed diagonal variance matrixskew_diag_mat
Simulate a structured correlation matrix with reduced rankstruc_cor_mat
Theoretical variogramtheoretical_variogram
Simulate genetic values based on an unstructured model for GxE interaction - `AlphaSimR` input parametersunstr_asr_input
Simulate genetic values based on an unstructured model for GxE interaction - Simulation with `AlphaSimR`unstr_asr_output