Function to simulate a step in a breeding scheme
breeding.diploid(
population,
mutation.rate = 10^-8,
remutation.rate = 10^-8,
recombination.rate = 1,
selection.m = NULL,
selection.f = NULL,
new.selection.calculation = TRUE,
selection.function.matrix = NULL,
selection.size = 0,
ignore.best = 0,
breeding.size = 0,
breeding.sex = NULL,
breeding.sex.random = FALSE,
relative.selection = FALSE,
class.m = 0,
class.f = 0,
add.gen = 0,
recom.f.indicator = NULL,
duplication.rate = 0,
duplication.length = 0.01,
duplication.recombination = 1,
new.class = 0L,
bve = FALSE,
sigma.e = NULL,
sigma.g = 100,
new.bv.child = NULL,
phenotyping.child = NULL,
relationship.matrix = "vanRaden",
relationship.matrix.ogc = "kinship",
computation.A = NULL,
computation.A.ogc = NULL,
delete.haplotypes = NULL,
delete.individuals = NULL,
fixed.breeding = NULL,
fixed.breeding.best = NULL,
max.offspring = Inf,
max.litter = Inf,
store.breeding.totals = FALSE,
forecast.sigma.g = TRUE,
multiple.bve = "add",
store.bve.data = FALSE,
fixed.assignment = FALSE,
reduce.group = NULL,
reduce.group.selection = "random",
selection.highest = c(TRUE, TRUE),
selection.criteria = NULL,
same.sex.activ = FALSE,
same.sex.sex = 0.5,
same.sex.selfing = FALSE,
selfing.mating = FALSE,
selfing.sex = 0.5,
praeimplantation = NULL,
heritability = NULL,
repeatability = NULL,
save.recombination.history = FALSE,
martini.selection = FALSE,
BGLR.bve = FALSE,
BGLR.model = "RKHS",
BGLR.burnin = 500,
BGLR.iteration = 5000,
BGLR.print = FALSE,
copy.individual = FALSE,
copy.individual.m = FALSE,
copy.individual.f = FALSE,
dh.mating = FALSE,
dh.sex = 0.5,
n.observation = NULL,
bve.0isNA = FALSE,
phenotype.bv = FALSE,
delete.same.origin = FALSE,
remove.effect.position = FALSE,
estimate.u = FALSE,
new.phenotype.correlation = NULL,
new.residual.correlation = NULL,
new.breeding.correlation = NULL,
estimate.add.gen.var = FALSE,
estimate.pheno.var = FALSE,
best1.from.group = NULL,
best2.from.group = NULL,
best1.from.cohort = NULL,
best2.from.cohort = NULL,
add.class.cohorts = TRUE,
store.comp.times = TRUE,
store.comp.times.bve = TRUE,
store.comp.times.generation = TRUE,
import.position.calculation = NULL,
BGLR.save = "RKHS",
BGLR.save.random = FALSE,
ogc = FALSE,
ogc.target = "min.sKin",
ogc.uniform = NULL,
ogc.ub = NULL,
ogc.lb = NULL,
ogc.ub.sKin = NULL,
ogc.lb.BV = NULL,
ogc.ub.BV = NULL,
ogc.eq.BV = NULL,
ogc.ub.sKin.increase = NULL,
ogc.lb.BV.increase = NULL,
emmreml.bve = FALSE,
rrblup.bve = FALSE,
sommer.bve = FALSE,
sommer.multi.bve = FALSE,
nr.edits = 0,
gene.editing.offspring = FALSE,
gene.editing.best = FALSE,
gene.editing.offspring.sex = c(TRUE, TRUE),
gene.editing.best.sex = c(TRUE, TRUE),
gwas.u = FALSE,
approx.residuals = TRUE,
sequenceZ = FALSE,
maxZ = 5000,
maxZtotal = 0,
delete.sex = 1:2,
gwas.group.standard = FALSE,
y.gwas.used = "pheno",
gen.architecture.m = 0,
gen.architecture.f = NULL,
add.architecture = NULL,
ncore = 1,
ncore.generation = 1,
Z.integer = FALSE,
store.effect.freq = FALSE,
backend = "doParallel",
randomSeed = NULL,
randomSeed.generation = NULL,
Rprof = FALSE,
miraculix = NULL,
miraculix.cores = 1,
miraculix.mult = NULL,
miraculix.chol = TRUE,
best.selection.ratio.m = 1,
best.selection.ratio.f = NULL,
best.selection.criteria.m = "bv",
best.selection.criteria.f = NULL,
best.selection.manual.ratio.m = NULL,
best.selection.manual.ratio.f = NULL,
best.selection.manual.reorder = TRUE,
bve.class = NULL,
parallel.generation = FALSE,
name.cohort = NULL,
display.progress = TRUE,
combine = FALSE,
repeat.mating = NULL,
repeat.mating.copy = NULL,
repeat.mating.fixed = NULL,
repeat.mating.overwrite = TRUE,
time.point = 0,
creating.type = 0,
multiple.observation = FALSE,
new.bv.observation = NULL,
new.bv.observation.gen = NULL,
new.bv.observation.cohorts = NULL,
new.bv.observation.database = NULL,
phenotyping = NULL,
phenotyping.gen = NULL,
phenotyping.cohorts = NULL,
phenotyping.database = NULL,
bve.gen = NULL,
bve.cohorts = NULL,
bve.database = NULL,
sigma.e.gen = NULL,
sigma.e.cohorts = NULL,
sigma.e.database = NULL,
sigma.g.gen = NULL,
sigma.g.cohorts = NULL,
sigma.g.database = NULL,
gwas.gen = NULL,
gwas.cohorts = NULL,
gwas.database = NULL,
bve.insert.gen = NULL,
bve.insert.cohorts = NULL,
bve.insert.database = NULL,
reduced.selection.panel.m = NULL,
reduced.selection.panel.f = NULL,
breeding.all.combination = FALSE,
depth.pedigree = 7,
depth.pedigree.ogc = 7,
copy.individual.keep.bve = TRUE,
copy.individual.keep.pheno = TRUE,
bve.avoid.duplicates = TRUE,
report.accuracy = TRUE,
share.genotyped = 1,
singlestep.active = FALSE,
remove.non.genotyped = TRUE,
added.genotyped = 0,
fast.uhat = TRUE,
offspring.bve.parents.gen = NULL,
offspring.bve.parents.database = NULL,
offspring.bve.parents.cohorts = NULL,
offspring.bve.offspring.gen = NULL,
offspring.bve.offspring.database = NULL,
offspring.bve.offspring.cohorts = NULL,
culling.gen = NULL,
culling.database = NULL,
culling.cohort = NULL,
culling.time = Inf,
culling.name = "Not_named",
culling.bv1 = 0,
culling.share1 = 0,
culling.bv2 = NULL,
culling.share2 = NULL,
culling.index = 0,
culling.single = TRUE,
culling.all.copy = TRUE,
calculate.reliability = FALSE,
selection.m.gen = NULL,
selection.f.gen = NULL,
selection.m.database = NULL,
selection.f.database = NULL,
selection.m.cohorts = NULL,
selection.f.cohorts = NULL,
selection.m.miesenberger = FALSE,
selection.f.miesenberger = NULL,
selection.miesenberger.reliability.est = "estimated",
miesenberger.trafo = 0,
multiple.bve.weights.m = 1,
multiple.bve.weights.f = NULL,
multiple.bve.scale.m = "bv_sd",
multiple.bve.scale.f = NULL,
verbose = TRUE,
bve.parent.mean = FALSE,
bve.grandparent.mean = FALSE,
bve.mean.between = "bvepheno",
bve.direct.est = TRUE,
bve.pseudo = FALSE,
bve.pseudo.accuracy = 1,
miraculix.destroyA = TRUE,
mas.bve = FALSE,
mas.markers = NULL,
mas.number = 5,
mas.effects = NULL,
threshold.selection = NULL,
threshold.sign = ">",
input.phenotype = "own",
bve.ignore.traits = NULL,
bv.ignore.traits = NULL,
genotyped.database = NULL,
genotyped.gen = NULL,
genotyped.cohorts = NULL,
genotyped.share = 1,
genotyped.array = 1,
sex.s = NULL,
bve.imputation = TRUE,
bve.imputation.errorrate = 0,
share.phenotyped = 1,
avoid.mating.fullsib = FALSE,
avoid.mating.halfsib = FALSE,
max.mating.pair = Inf,
bve.per.sample.sigma.e = TRUE,
bve.solve = "exact"
)Population list
Mutation rate in each marker (default: 10^-8)
Remutation rate in each marker (default: 10^-8)
Average number of recombination per 1 length unit (default: 1M)
Selection criteria for male individuals (Set to "random" to randomly select individuals - this happens automatically when no the input in selection.criteria has no input ((usually breeding values)))
Selection criteria for female individuals (default: selection.m , alt: "random", function")
If TRUE recalculate breeding values obtained by selection.function.matrix
Manuel generation of a temporary selection function (Use BVs instead!)
Number of selected individuals for breeding (default: c(0,0) - alt: positive numbers)
Not consider the top individuals of the selected individuals (e.g. to use 2-10 best individuals)
Number of individuals to generate
Share of female animals (if single value is used for breeding size; default: 0.5)
If TRUE randomly chose sex of new individuals (default: FALSE - use expected values)
Use best.selection.ratio instead!
Migrationlevels of male individuals to consider for mating process (default: 0)
Migrationlevels of female individuals to consider for mating process (default: 0)
Generation you want to add the new individuals to (default: New generation)
Use step function for recombination map (transform snp.positions if possible instead)
Share of recombination points with a duplication (default: 0 - DEACTIVATED)
Average length of a duplication (Exponentially distributed)
Average number of recombinations per 1 length uit of duplication (default: 1)
Migration level of newly generated individuals (default: 0)
If TRUE perform a breeding value estimation (default: FALSE)
Enviromental variance (default: 100)
Genetic variance (default: 100 - only used if not computed via estimate.sigma.g^2 in der Zuchtwertschaetzung (Default: 100)
(OLD! - use phenotyping.child) Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0)
Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0)
Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM")
Method to calculate relationship matrix for OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM")
(OLD! - use relationship.matrix) Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM")
(OLD! use relationship.matrix.ogc) Method to calculate pedigree matrix in OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM")
Generations for with haplotypes of founders can be deleted (only use if storage problem!)
Generations for with individuals are completley deleted (only use if storage problem!)
Set of targeted matings to perform
Perform targeted matings in the group of selected individuals
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w))
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w))
If TRUE store information on selected animals in $info$breeding.totals
Set FALSE to not estimate sigma.g (Default: TRUE)
Way to handle multiple traits in bv/selection (default: "add", alt: "ranking")
If TRUE store information of bve in $info$bve.data
Set TRUE for targeted mating of best-best individual till worst-worst (of selected). set to "bestworst" for best-worst mating
(OLD! - use culling modules) Groups of animals for reduce to a new size (by changing class to -1)
(OLD! - use culling modules) Selection criteria for reduction of groups (cf. selection.m / selection.f - default: "random")
If 0 individuals with lowest bve are selected as best individuals (default c(1,1) - (m,w))
What to use in the selection proces (default: "bve", alt: "bv", "pheno")
If TRUE allow matings of individuals of same sex
Probability to use female individuals as parents (default: 0.5)
Set to TRUE to allow for selfing when using same.sex matings
If TRUE generate new individuals via selfing
Share of female individuals used for selfing (default: 0.5)
Only use matings the lead to a specific genotype in a specific marker
Use sigma.e to obtain a certain heritability (default: NULL)
Set this to control the share of the residual variance (sigma.e) that is permanent (there for each observation)
If TRUE store the time point of each recombination event
If TRUE use the group of non-selected individuals as second parent
If TRUE use BGLR to perform breeding value estimation
Select which BGLR model to use (default: "RKHS", alt: "BRR", "BL", "BayesA", "BayesB", "BayesC")
Number of burn-in steps in BGLR (default: 1000)
Number of iterations in BGLR (default: 5000)
If TRUE set verbose to TRUE in BGLR
If TRUE copy the selected father for a mating
If TRUE generate exactly one copy of all selected male in a new cohort (or more by setting breeding.size)
If TRUE generate exactly one copy of all selected female in a new cohort (or more by setting breeding.size)
If TRUE generate a DH-line in mating process
Share of DH-lines generated from selected female individuals
Number of phenotypes generated per individuals (influences enviromental variance)
Individuals with phenotype 0 are used as NA in breeding value estimation
If TRUE use phenotype as estimated breeding value
If TRUE delete recombination points when genetic origin of adjacent segments is the same
If TRUE remove real QTLs in breeding value estimation
If TRUE estimate u in breeding value estimation (Y = Xb + Zu + e)
(OLD! - use new.residual.correlation!) Correlation of the simulated enviromental variance
Correlation of the simulated enviromental variance
Correlation of the simulated genetic variance (child share! heritage is not influenced!)
If TRUE estimate additive genetic variance and heritability based on parent model
If TRUE estimate total variance in breeding value estimation
(OLD!- use selection.m.database) Groups of individuals to consider as First Parent / Father (also female individuals are possible)
(OLD!- use selection.f.database) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible)
(OLD!- use selection.m.cohorts) Groups of individuals to consider as First Parent / Father (also female individuals are possible)
(OLD! - use selection.f.cohorts) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible)
Migration levels of all cohorts selected for reproduction are automatically added to class.m/class.f (default: TRUE)
If TRUE store computation times in $info$comp.times (default: TRUE)
If TRUE store computation times of breeding value estimation in $info$comp.times.bve (default: TRUE)
If TRUE store computation times of mating simulations in $info$comp.times.generation (default: TRUE)
Function to calculate recombination point into adjacent/following SNP
Method to use in BGLR (default: "RKHS" - alt: NON currently)
Add random number to store location of internal BGLR computations (only needed when simulating a lot in parallel!)
If TRUE use optimal genetic contribution theory to perform selection ( This requires the use of the R-package optiSel)
Target of OGC (default: "min.sKin" - minimize inbreeding; alt: "max.BV" / "min.BV" - maximize genetic gain; both under constrains selected below)
This corresponds to the uniform constrain in optiSel
This corresponds to the ub constrain in optiSel
This corresponds to the lb constrain in optiSel
This corresponds to the ub.sKin constrain in optiSel
This corresponds to the lb.BV constrain in optiSel
This corresponds to the ub.BV constrain in optiSel
This corresponds to the eq.BV constrain in optiSel
This corresponds to the upper bound (current sKin + ogc.ub.sKin.increase) as ub.sKin in optiSel
This corresponds to the lower bound (current BV + ogc.lb.BV.increase) as lb.BV in optiSel
If TRUE use REML estimator from R-package EMMREML in breeding value estimation
If TRUE use REML estimator from R-package rrBLUP in breeding value estimation
If TRUE use REML estimator from R-package sommer in breeding value estimation
Set TRUE to use a mulit-trait model in the R-package sommer for BVE
Number of edits to perform per individual
If TRUE perform gene editing on newly generated individuals
If TRUE perform gene editing on selected individuals
Which sex to perform editing on (Default c(TRUE,TRUE), mw)
Which sex to perform editing on (Default c(TRUE,TRUE), mw)
If TRUE estimate u via GWAS (relevant for gene editing)
If FALSE calculate the variance for each marker separatly instead of using a set variance (doesnt change order - only p-values)
Split genomic matric into parts (relevent if high memory usage)
Number of SNPs to consider in each part of sequenceZ
Number of matrix entries to consider jointly (maxZ = maxZtotal/number of animals)
Remove all individuals from these sex from generation delete.individuals (default: 1:2 ; note:delete individuals=NULL)
If TRUE standardize phenotypes by group mean
What y value to use in GWAS study (Default: "pheno", alt: "bv", "bve")
Genetic architecture for male animal (default: 0 - no transformation)
Genetic architecture for female animal (default: gen.architecture.m - no transformation)
List with two vectors containing (A: length of chromosomes, B: position in cM of SNPs)
Cores used for parallel computing in compute.snps
Number of cores to use in parallel generation
If TRUE save Z as a integer in parallel computing
If TRUE store the allele frequency of effect markers per generation
Chose the used backend (default: "doParallel", alt: "doMPI")
Set random seed of the process
Set random seed for parallel generation process
Store computation times of each function
If TRUE use miraculix to perform computations (ideally already generate population in creating.diploid with this; default: automatic detection from population list)
Number of cores used in miraculix applications (default: 1)
If TRUE use miraculix for matrix multiplications even if miraculix is not used for storage
Set to FALSE to deactive miraculix based Cholesky-decomposition (default: TRUE)
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1)
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1)
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno")
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno")
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7))
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7))
Set to FALSE to not use the order from best to worst selected individual but plain order based on database-order
Consider only animals of those class classes in breeding value estimation (default: NULL - use all)
Set TRUE to active parallel computing in animal generation
Name of the newly added cohort
Set FALSE to not display progress bars. Setting verbose to FALSE will automatically deactive progress bars
Copy existing individuals (e.g. to merge individuals from different groups in a joined cohort). Individuals to use are used as the first parent
Generate multiple mating from the same dam/sire combination (first column: number of offspring; second column: probability)
Generate multiple copies from a copy action (combine / copy.individuals.m/f) (first column: number of offspring; second column: probability)
Vector containing number of times each mating is repeated. This will overwrite sampling from repeat.mating / repeat.mating.copy (default: NULL)
Set to FALSE to not use the current repeat.mating / repeat.mating.copy input as the new standard values (default: TRUE)
Time point at which the new individuals are generated
Technique to generate new individuals (usage in web-based application)
Set TRUE to allow for more than one phenotype observation per individual (this will decrease enviromental variance!)
(OLD! - use phenotyping) Quick acces to phenotyping for (all: "all", non-phenotyped: "non_obs", non-phenotyped male: "non_obs_m", non-phenotyped female: "non_obs_f")
(OLD! use phenotyping.gen) Vector of generation from which to generate additional phenotypes
(OLD! use phenotyping.cohorts)Vector of cohorts from which to generate additional phenotype
(OLD! use phenotyping.database) Matrix of groups from which to generate additional phenotypes
Quick acces to phenotyping for (all: "all", non-phenotyped: "non_obs", non-phenotyped male: "non_obs_m", non-phenotyped female: "non_obs_f")
Vector of generation from which to generate additional phenotypes
Vector of cohorts from which to generate additional phenotype
Matrix of groups from which to generate additional phenotypes
Generations of individuals to consider in breeding value estimation (default: NULL)
Cohorts of individuals to consider in breeding value estimation (default: NULL)
Groups of individuals to consider in breeding value estimation (default: NULL)
Generations to consider when estimating sigma.e when using hertability
Cohorts to consider when estimating sigma.e when using hertability
Groups to consider when estimating sigma.e when using hertability
Generations to consider when estimating sigma.g
Cohorts to consider when estimating sigma.g
Groups to consider when estimating sigma.g
Generations to consider in GWAS analysis
Cohorts to consider in GWAS analysis
Groups to consider in GWAS analysis
Generations of individuals to compute breeding values for (default: all groups in bve.database)
Cohorts of individuals to compute breeding values for (default: all groups in bve.database)
Groups of individuals to compute breeding values for (default: all groups in bve.database)
Use only a subset of individuals of the potential selected ones ("Split in user-interface")
Use only a subset of individuals of the potential selected ones ("Split in user-interface")
Set to TRUE to automatically perform each mating combination possible exactly ones.
Depth of the pedigree in generations (default: 7)
Depth of the pedigree in generations (default: 7)
Set to FALSE to not keep estimated breeding value in case of use of copy.individuals
Set to FALSE to not keep estimated breeding values in case of use of copy.individuals
If set to FALSE multiple generatations of the same individual can be used in the bve (only possible by using copy.individual to generate individuals)
Report the accuracy of the breeding value estimation
Share of individuals newly generated individuals that are genotyped
Set TRUE to use single step in breeding value estimation (only implemented for vanRaden- G matrix and without use sequenceZ) (Legarra 2014)
Set to FALSE to manually include non-genotyped individuals in genetic BVE, single-step will deactive this as well
Share of individuals that is additionally genotyped (only for copy.individuals)
Set to FALSE to derive inverse of A in rrBLUP
Generations to consider to derive phenotype from offspring phenotypes
Groups to consider to derive phenotype from offspring phenotypes
Cohorts to consider to derive phenotype from offspring phenotypes
Active generations for import of offspring phenotypes
Active groups for import of offspring phenotypes
Active cohorts for import of offspring phenotypes
Generations to consider to culling
Groups to consider to culling
Cohort to consider to culling
Age of the individuals at culling
Name of the culling action (user-interface stuff)
Reference Breeding value
Probability of death for individuals with bv1
Alternative breeding value (linear extended for other bvs)
Probability of death for individuals with bv2
Genomic index (default:0 - no genomic impact, use: "lastindex" to use the last selection index applied in selection)
Set to FALSE to not apply the culling module on all individuals of the cohort
Set to FALSE to not kill copies of the same individual in the culling module
Set TRUE to calculate a reliability when performing Direct-Mixed-Model BVE
Generations available for selection of paternal parent
Generations available for selection of maternal parent
Groups available for selection of paternal parent
Groups available for selection of maternal parent
Cohorts available for selection of paternal parent
Cohorts available for selection of maternal parent
Use Weighted selection index according to Miesenberger 1997 for paternal selection
Use Weighted selection index according to Miesenberger 1997 for maternal selection
If available reliability estimated are used. If not use default:"estimated" (SD BVE / SD Pheno), alt: "heritability", "derived" (cor(BVE,BV)^2) as replacement
Ignore all eigenvalues below this threshold and apply dimension reduction (default: 0 - use all)
Weighting between traits when using "add" (default: 1)
Weighting between traits when using "add" (default: same as multiple.bve.weights.m)
Default: "bv_sd"; Set to "pheno_sd" when using gains per phenotypic SD, "unit" when using gains per unit, "bve" when using estimated breeding values
Default: "bv_sd"; Set to "pheno_sd" when using gains per phenotypic SD, "unit" when using gains per unit, "bve" when using estimated breeding values
Set to FALSE to not display any prints
Set to TRUE to use the average parental performance as the breeding value estimate
Set to TRUE to use the average grandparental performance as the breeding value estimate
Select if you want to use the "bve", "bv", "pheno" or "bvepheno" to form the mean (default: "bvepheno" - if available bve, else pheno)
If TRUE predict BVEs in direct estimation according to vanRaden 2008 method 2 (default: TRUE)
If set to TRUE the breeding value estimation will be simulated with resulting accuracy bve.pseudo.accuracy (default: 1)
The accuracy to be obtained in the "pseudo" - breeding value estimation
If FALSE A will not be destroyed in the process of inversion (less computing / more memory)
If TRUE use marker assisted selection in the breeding value estimation
Vector containing markers to be used in marker assisted selection
If no markers are provided this nr of markers is selected (if single marker QTL are present highest effect markers are prioritized)
Effects assigned to the MAS markers (Default: estimated via lm())
Minimum value in the selection index selected individuals have to have
Pick all individuals above (">") the threshold. Alt: ("<", "=", "<=", ">=")
Select what to use in BVE (default: own phenotype ("own"), offspring phenotype ("off"), their average ("mean") or a weighted average ("weighted"))
Vector of traits to ignore in the breeding value estimation (default: NULL, use: "zero" to not consider traits with 0 index weight in multiple.bve.weights.m/.w)
Vector of traits to ignore in the calculation of the genomic value (default: NULL; Only recommended for high number of traits and experienced users!)
Groups to generate genotype data (that can be used in a BVE)
Generations to generate genotype data (that can be used in a BVE)
Cohorts to generate genotype data (that can be used in a BVE)
Share of individuals in genotyped.gen/database/cohort to generate genotype data from (default: 1)
Genotyping array used
Specify which newly added individuals are male (1) or female (2)
Set to FALSE to not perform imputation up to the highest marker density of genotyping data that is available
Share of errors in the imputation procedure (default: 0)
Share of the individuals to phenotype
Set to TRUE to not generate offspring of full siblings
Set to TRUE to not generate offspring from half or full siblings
Set to the maximum number of matings between two individuals (default: Inf)
Set to FALSE to deactivate the use of a heritablity based on the number of observations generated per sample
Provide solver to be used in BVE (default: "exact" solution via inversion, alt: "pcg", function with inputs A, b and output y_hat)
Population-list
# NOT RUN {
population <- creating.diploid(nsnp=1000, nindi=100)
population <- breeding.diploid(population, breeding.size=100, selection.size=c(25,25))
# }
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