Package: simplePHENOTYPES 2.0.0.9003

simplePHENOTYPES: Simulation of Pleiotropic, Linked and Epistatic Phenotypes

The number of studies involving correlated traits and the availability of tools to handle this type of data has increased considerably in the last decade. With such a demand, we need tools for testing hypotheses related to single and multi-trait (correlated) phenotypes based on many genetic settings. Thus, we implemented various options for simulation of pleiotropy and Linkage Disequilibrium under additive, dominance and epistatic models. The simulation currently takes a marker data set as an input and then uses it for simulating multiple traits as described in Fernandes and Lipka (2020) <doi:10.1186/s12859-020-03804-y>.

Authors:Samuel Fernandes [aut, cre], Alexander Lipka [aut]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
simplePHENOTYPES/json (API)

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

Bug tracker:https://github.com/samuelbfernandes/simplephenotypes/issues

On CRAN:

Conda:

pleiotropysimulationrustcargo

7.35 score 17 stars 63 scripts 456 downloads 1 mentions 63 exports 3 dependencies

Last updated from:3c000630a5. Checks:10 OK, 5 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
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linux-devel-x86_64OK1334
source / vignettesOK296
linux-release-arm64OK1209
linux-release-x86_64OK1366
macos-release-arm64OK1099
macos-release-x86_64OK2150
macos-oldrel-arm64OK1293
macos-oldrel-x86_64OK2366
windows-devel-arm64ERROR1591
windows-devel-x86_64ERROR1764
windows-release-arm64ERROR1616
windows-release-x86_64ERROR1532
windows-oldrel-x86_64ERROR1710
wasm-releaseOK126

Exports:a_matrixadditiveadditive_valueas_numericas_populationbreed_compositionbulkcoheritabilitycombining_abilitycomplex_phenotypescor_ar1create_phenotypescrosscross_usefulnesscrossbreeddominancedosagesdouble_haploidepistasisfamiliesfilter_genofounders_coalescentg_matrixgenetic_valuesgenotypic_valuegxe_valuehaplotypesheterosisliability_thresholdmabc_selectmarker_selectmatemating_designmediation_splitn_individualsobserve_countsoptimum_contributionparentagepedigreephenotype_valuephenotypes_longphenotypes_widepopulation_from_haplotypespopulation_traitpredict_ebvprediction_accuracyprogeny_testqtn_tablerecurrent_parent_recoveryrecurrent_selectionsample_parentsselect_indselection_methodsselfcrosssimulate_phenotypesimulate_transcriptomesingle_seed_descentsynthetic_maptemplate_effectstranscriptomevqtlwrite_phenotypeswrite_qtn_table

Dependencies:data.tablemvtnormrlang

Complete reference: every option in one place
1. Genotype input | Converting from other formats | Filtering markers with filter_geno() | 2. The genetic map | 3. The simulation grammar | Every layer | Layer options | Replications and per-trait proportions | One call instead of a pipe | Fine control: fixed loci, phase, means, subsets | 4. Genetic architectures | Independent | Pleiotropy with a target genetic correlation | Linkage disequilibrium | Combining architectures | 5. Breeding populations | Crossing, selfing, doubled haploids | Recurrent selfing | Reproducibility | Phenotyping a pedigree | 6. Inspecting a simulation | 7. Output | In memory | Written to disk | 8. Transcriptome and expression-mediated phenotypes | Simulating expression | A phenotype from expression | Genetic and environmental mediation | Without genotypes | Reusing an architecture in a new population | Calibrating to observed expression | RNA-seq counts | 9. Original implementation of create_phenotypes | Session information
Rendered fromcomplete-reference.Rmdusingknitr::rmarkdown

Last update: 2026-10-07
Started: 2026-09-10

Genetic maps and recombination
Why base pairs are not enough | synthetic_map() | What the model does | Tuning it | Using a real map | How the map changes results | Session information
Rendered fromgenetic-maps.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2026-09-10

Simulating breeding populations
Before you start: you need a genetic map | Founders | Working with a Population | Your first cross | Selfing | Doubled haploids | Backcrossing | Recurrent selfing: from an F1 to inbred lines | Checking the simulation is doing what you think | Reproducibility | Phenotyping a pedigree | A complete example | Common problems | Session information
Rendered frombreeding-populations.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2026-09-10

Migrating from v1 create_phenotypes() to the v2 grammar
Single trait | Pleiotropy | Partial pleiotropy | Spurious pleiotropy (LD) | Choosing the QTNs yourself | Variance explained by each QTN | Output formats | Reading genotypes from files | Residual correlation | Not yet in the grammar
Rendered fromv1-to-v2.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-09-10

The simplePHENOTYPES v2 grammar
The example data | The genetic map | Reading genotype data | Simulating phenotypes: the grammar | Dominance, epistasis and variance QTL | Multiple traits and genetic correlation | Linked, not pleiotropic: the "ld" architecture | Combining architectures | One call instead of a pipe | Writing results | Multi-generation crosses | Original implementation of create_phenotypes | Session information
Rendered fromsimplePHENOTYPES-v2.Rmdusingknitr::rmarkdown

Last update: 2026-10-01
Started: 2026-09-07

Original implementation of create_phenotypes
Load Sample Data set | Single Trait | Multiple Traits: Pleiotropy Architecture | Multiple Traits: Partial Pleiotropy Architecture | Multiple Traits: Spurious Pleiotropy Architecture | Multiple Traits: Partial Pleiotropy Architecture with other useful parameters | Using Selected Markers to be QTN | Using Multiple Marker Data Files
Rendered fromsimplePHENOTYPES.Rmdusingknitr::rmarkdown

Last update: 2026-09-10
Started: 2019-09-26

Readme and manuals

Help Manual

Help pageTopics
Subset the individuals of a Population[.Population
Numerator relationship matrix from the recorded pedigreea_matrix
Add an additive variance componentadditive
Additive genetic value on a fixed, cross-generational scaleadditive_value
Convert genotypes to numeric codingas_numeric
Create a population of phased individuals from genotype dataas_population
Expected breed composition from the pedigreebreed_composition
Bulk advancebulk
Pool populations that share a genetic mapc.Population
Co-heritability between traitscoheritability
Combining ability: GCA, SCA and testcross meritcombining_ability
Combine single-architecture models under a common heritabilitycomplex_phenotypes
AR(1) correlation matrixcor_ar1
Simulation of single/multiple traits under different models and genetic architectures.create_phenotypes
Cross two individualscross
Predict the usefulness of candidate crossescross_usefulness
Crossbreeding systemscrossbreed
Add a dominance variance componentdominance
Dosage matrix of a Populationdosages
Produce doubled haploids from an individualdouble_haploid
Add an epistatic variance componentepistasis
Family groupings from the recorded pedigreefamilies
Filter a genotype object by MAF, heterozygosity and LDfilter_geno
Founder haplotypes from a coalescent with recombinationfounders_coalescent
Genomic relationship matrix (VanRaden 2008)g_matrix
Genetic values behind the simulated phenotypesgenetic_values
Total genotypic value on a fixed, cross-generational scalegenotypic_value
Genotype-by-environment slope on a fixed, cross-generational scalegxe_value
The phased haplotypes of a populationhaplotypes
Heterosis on a frozen additive + dominance architectureheterosis
Categorical phenotypes from a liability-threshold modelliability_threshold
Marker-assisted backcross selectionmabc_select
Marker-assisted selection and gene pyramidingmarker_select
Execute a mating planmate
Build a mating planmating_design
Genetic-mediated vs environmental split of a derived transcriptome componentmediation_split
Number of individuals in a Populationn_individuals
Draw RNA-seq counts from a simulated transcriptomeobserve_counts
Optimum contribution selectionoptimum_contribution
Parentage of a Population's individualsparentage
Pedigree selectionpedigree
Phenotype on a fixed, cross-generational scalephenotype_value
Realized phenotypes in long formatphenotypes_long
Realized phenotypes in wide formatphenotypes_wide
Diagnostic plots for a simulated phenotypeplot.phenotype_sim
Create a population from phased haplotypespopulation_from_haplotypes
The trait a Population carriespopulation_trait
Predicted breeding values by BLUP with known variance componentspredict_ebv
Apply a fixed transcriptome architecture to a new populationpredict.transcriptome_sim
Accuracy of predicted breeding valuesprediction_accuracy
Progeny test: score parents by the mean of their progenyprogeny_test
The QTNs behind a simulation, with their effectsqtn_table
Marker-observed recovery of the recurrent-parent genomerecurrent_parent_recovery
Recurrent selectionrecurrent_selection
Draw parents for mating in proportion to OCS contributionssample_parents
Select individuals from a simulated populationselect_ind
The engine's selection operators, as a manifestselection_methods
Self-pollinate an individualselfcross
Start a phenotype simulation (v2 grammar foundation)simulate_phenotype
Simulate a genetically controlled transcriptomesimulate_transcriptome
Single seed descentsingle_seed_descent
Build a synthetic genetic map from physical marker positionssynthetic_map
Realized-scale additive and dominance effects of a simulationtemplate_effects
Transcriptome layer: a phenotype component driven by gene expressiontranscriptome
Add a variance-QTL (vQTL) componentvqtl
Write realized phenotypes to diskwrite_phenotypes
Write the QTN table of a simulation to diskwrite_qtn_table