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The successor to the 'AlphaSim' software for breeding program simulation (Faux et al., 2016; https://doi.org/10.3835/plantgenome2016.02.0013). Used for stochastic simulations of breeding programs to the level of DNA sequence for every individual. Contained is a wide range of functions for modeling common tasks in a breeding program, such as selection and crossing. These functions allow for constructing simulations of highly complex plant and animal breeding programs via scripting in the R software environment. Such simulations can be used to evaluate overall breeding program performance and conduct research into breeding program design, such as implementation of genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS') for fast simulation of biallelic sequences according to a population demographic history (Chen et al., 2009; https://doi.org/10.1101/gr.083634.108).

Publication

Gaynor, R. Chris, Gregor Gorjanc, and John M. Hickey. 2021. AlphaSimR: an R package for breeding program simulations. G3 Gene|Genomes|Genetics 11(2):jkaa017. https://doi.org/10.1093/g3journal/jkaa017.

Download

AlphaSimR is available on CRAN.

To install use:

install.packages('AlphaSimR')

The development version of AlphaSimR (potentially unstable) can be accessed from the devel branch on GitHub.

To install use:

devtools::install_github(repo="gaynorr/AlphaSimR@devel")

To install with vignettes use:

devtools::install_github(repo="gaynorr/AlphaSimR@devel", build_vignettes=TRUE)

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Version

Install

install.packages('AlphaSimR')

Monthly Downloads

2,797

Version

2.1.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/gaynorr/AlphaSimR

Homepage

https://gaynorr.github.io/AlphaSimR/

Maintainer

Chris Gaynor

Last Published

November 8th, 2025

Functions in AlphaSimR (2.1.0)

Multi-Population

NamedMapPop-class

Raw population with genetic map and id

RR-BLUP GCA Model 2

RR-BLUP with Dominance Model 2

RR-BLUP SCA Model 2

RR-BLUP Model with Dominance

RR-BLUP GCA Model

Simulation parameters

RR-BLUP SCA Model

Additive, dominance and GxE trait

TraitADEG-class

Additive, dominance, epistasis, and GxE trait

Sex specific additive trait

RR-BLUP Solution

Sex specific additive and dominance trait

Additive and dominance trait

Additive and GxE trait

Additive-by-additive epistatic deviations

Convert a normal (Gaussian) trait to an ordered categorical (threshold) trait

Additive, dominance, and epistatic trait

Calculate phenotypes

Lose individuals at random

Combine MapPop chromosomes

Find individuals of desired sex

Double the ploidy of individuals

Additive and epistatic trait

Additive, epistasis and GxE trait

Number of available threads

editGenomeTopQtl

Edit genome - the top QTL

Add residual error to genetic values

Add segregating site to MapPop

Create new population

Dominance deviations

Estimated breeding value

Total genic variance

Dominance genic variance

Import genetic map

Hybrid crossing

Determine families

Test if individuals of a population are female or male

Get genetic map

Identify candidate individuals

findLociMapSuperset

Find LociMap superset

Test if object is of a Population class

Mean estimated breeding values

Mean genetic values

Combine genomes of individuals

convertTraitsToNames

Convert traits to a vector of names

Make designed crosses

Make designed crosses

Create new Multi Population

Additive genic variance

pullMarkerHaplo

Pull marker haplotypes

Retrieves marker names from genMap

Pull marker genotypes

Create new population

Additive-by-additive genic variance

Merge list of populations

Find trait QTL index

Population variance

Calculate parent average

Get SNP genetic map

Returns a vector response from a population

Sumarize genetic parameters

Get QTL genetic map

Pull QTL haplotypes

Pull QTL genotypes

Import haplotypes

mendelianSampling

Calculate Mendelian sampling

Mean phenotypic values

importInbredGeno

Import inbred, diploid genotypes

pullSegSiteHaplo

Pull seg site haplotypes

pullSegSiteGeno

Pull segregating site genotypes

Make random crosses

Generates DH lines

Pull IBD haplotypes

Population variance

Quick founder haplotype simulation

Finds positions of loci by marker name

Add Random Mutations

Number of individuals

Make random crosses

Find loci on specific chromosomes

Select individuals

Create individuals with reduced ploidy

Reset population

Pull SNP haplotypes

Alternative wrapper for MaCS

Create founder haplotypes using MaCS

Pull SNP genotypes

Solve Multivariate Model

Sample haplotypes from a MapPop

Sample epistatic effects

Sample normal deviates using a seed

Solve RR-BLUP with EM

Set estimated breeding values (EBV)

Self individuals

Creates an empty population

Set marker haplotypes

solveRRBLUP_EM2

Solve RR-BLUP with EM and 2 random effects

solveRRBLUP_EM3

Solve RR-BLUP with EM and 3 random effects

Solve Univariate Model

Select and randomly cross

Select families

Selection index

Selection intensity

Additive variance

Writes a Pop-class as PLINK files

Additive-by-additive epistatic variance

Sample additive effects

Sample dominance effects

selectWithinFam

Select individuals within families

Select open pollinating plants

Write data records

Calculate Smith-Hazel weights

Solve Multikernel Model

Usefulness criterion

Linear transformation matrix

Dominance variance

Variance of estimated breeding values

Set GCA as phenotype

setPhenoProgTest

Set progeny test as phenotype

Solve Multikernel RR-BLUP

Total genetic variance

Solve Multivariate RR-BLUP

Phenotypic variance

AlphaSimR-package

AlphaSimR: Breeding Program Simulations

RR-BLUP Model 2

Raw population with genetic map

RRBLUP Memory Usage

HybridPop-class

Hybrid population