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BreedingSchemeLanguage

R/package "BreedingSchemeLanguage" It is difficult for plant breeders to determine an optimal breeding strategy given that the problem involves many factors, such as target trait genetic architecture and breeding resource availability. There are many possible breeding schemes for each breeding program. Although simulation study may be useful to help choose a better (or the best) breeding scheme, it is difficult for breeders to take the first step in conducting breeding simulation because of the complexity of building a simulation platform or even using existing simulation tools. We present here a simple and flexible simulation platform, the breeding scheme language (BSL). This simulation platform works in the statistical computing environment R. Users define their target species, trait genetic architectures, and breeding schemes by writing simple, self- explanatory scripts. We believe the BSL will be useful for breeders to evaluate breeding schemes and to choose an optimal breeding strategy among a number of possible ones, as well as for training plant breeders. A full manual is available at https://github.com/jeanlucj/BreedingSchemeLanguage/blob/master/inst/Manual.pdf

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Version

Install

install.packages('BreedingSchemeLanguage')

Monthly Downloads

3

Version

0.9.6

License

GPL-3

Maintainer

Jean-Luc Jannink

Last Published

October 22nd, 2018

Functions in BreedingSchemeLanguage (0.9.6)

testParameterOptimality

Function to return the optimality of a parameter vector for a breeding scheme given a simulation environment
makeGamete

makeGamete
predGameteMeanVar

predGameteMeanVar
makeMap

create map and QTL effects
genotype

Genotype markers
predictValue

Genomic prediction
doubledHaploid

Doubled haploids
getCoalescentSim

getCoalescentSim
randomMateNoFam

randomMateNoFam
select

Select individuals
makeProgenies

makeProgenies
makeSelfs

makeSelfs
outputResults

Save the results
pedigreeMate

pedigreeMate
phasedHapMap2mat

Transform a data.frame with a hapmap data in it into a marker dosage and map list
initializePopulation

Create a founder population
makeDHs

makeDHs
makeProgeny

makeProgeny
phenotype

Evaluate the phenotypic value
randomMate

randomMate
randomMateAll

randomMateAll
plotData

Plot the results
selfFertilize

Self-fertilize
simHapMap

Generate a data.frame with a hapmap data in it to test phasedHapMap2mat
calcAmatrix

Calculate an additive relationship matrix
calcPhenotypicValue

calcPhenotypicValue
calcGenotypicValue

calcGenotypicValue
cross

Cross with random mating, or equal contributions, or randomly between two populations
defineVariances

Define genetic, interaction, and error variances
DH

DH
defineCosts

Define the costs that go into breeding Default for some costs is zero because they probably belong to fixed costs
defineSpecies

Define and create species
addProgenyData

Add progeny information to data after cross, doubledHaploid, or selfFertilize