breeding.diploid: Breeding function
In MoBPS: Modular Breeding Program Simulator
Description
Usage
Arguments
Value
Examples
View source: R/breeding.diploid.R
Description
Function to simulate a step in a breeding scheme
Usage
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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"
)
Arguments
population
Population list
mutation.rate
Mutation rate in each marker (default: 10^-8)
remutation.rate
Remutation rate in each marker (default: 10^-8)
recombination.rate
Average number of recombination per 1 length unit (default: 1M)
selection.m
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.f
Selection criteria for female individuals (default: selection.m , alt: "random", function")
new.selection.calculation
If TRUE recalculate breeding values obtained by selection.function.matrix
selection.function.matrix
Manuel generation of a temporary selection function (Use BVs instead!)
selection.size
Number of selected individuals for breeding (default: c(0,0) - alt: positive numbers)
ignore.best
Not consider the top individuals of the selected individuals (e.g. to use 2-10 best individuals)
breeding.size
Number of individuals to generate
breeding.sex
Share of female animals (if single value is used for breeding size; default: 0.5)
breeding.sex.random
If TRUE randomly chose sex of new individuals (default: FALSE - use expected values)
relative.selection
Use best.selection.ratio instead!
class.m
Migrationlevels of male individuals to consider for mating process (default: 0)
class.f
Migrationlevels of female individuals to consider for mating process (default: 0)
add.gen
Generation you want to add the new individuals to (default: New generation)
recom.f.indicator
Use step function for recombination map (transform snp.positions if possible instead)
duplication.rate
Share of recombination points with a duplication (default: 0 - DEACTIVATED)
duplication.length
Average length of a duplication (Exponentially distributed)
duplication.recombination
Average number of recombinations per 1 length uit of duplication (default: 1)
new.class
Migration level of newly generated individuals (default: 0)
bve
If TRUE perform a breeding value estimation (default: FALSE)
sigma.e
Enviromental variance (default: 100)
sigma.g
Genetic variance (default: 100 - only used if not computed via estimate.sigma.g^2 in der Zuchtwertschaetzung (Default: 100)
new.bv.child
(OLD! - use phenotyping.child) Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0)
phenotyping.child
Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0)
relationship.matrix
Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM")
relationship.matrix.ogc
Method to calculate relationship matrix for OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM")
computation.A
(OLD! - use relationship.matrix) Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM")
computation.A.ogc
(OLD! use relationship.matrix.ogc) Method to calculate pedigree matrix in OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM")
delete.haplotypes
Generations for with haplotypes of founders can be deleted (only use if storage problem!)
delete.individuals
Generations for with individuals are completley deleted (only use if storage problem!)
fixed.breeding
Set of targeted matings to perform
fixed.breeding.best
Perform targeted matings in the group of selected individuals
max.offspring
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w))
max.litter
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w))
store.breeding.totals
If TRUE store information on selected animals in $info$breeding.totals
forecast.sigma.g
Set FALSE to not estimate sigma.g (Default: TRUE)
multiple.bve
Way to handle multiple traits in bv/selection (default: "add", alt: "ranking")
store.bve.data
If TRUE store information of bve in $info$bve.data
fixed.assignment
Set TRUE for targeted mating of best-best individual till worst-worst (of selected). set to "bestworst" for best-worst mating
reduce.group
(OLD! - use culling modules) Groups of animals for reduce to a new size (by changing class to -1)
reduce.group.selection
(OLD! - use culling modules) Selection criteria for reduction of groups (cf. selection.m / selection.f - default: "random")
selection.highest
If 0 individuals with lowest bve are selected as best individuals (default c(1,1) - (m,w))
selection.criteria
What to use in the selection proces (default: "bve", alt: "bv", "pheno")
same.sex.activ
If TRUE allow matings of individuals of same sex
same.sex.sex
Probability to use female individuals as parents (default: 0.5)
same.sex.selfing
Set to TRUE to allow for selfing when using same.sex matings
selfing.mating
If TRUE generate new individuals via selfing
selfing.sex
Share of female individuals used for selfing (default: 0.5)
praeimplantation
Only use matings the lead to a specific genotype in a specific marker
heritability
Use sigma.e to obtain a certain heritability (default: NULL)
repeatability
Set this to control the share of the residual variance (sigma.e) that is permanent (there for each observation)
save.recombination.history
If TRUE store the time point of each recombination event
martini.selection
If TRUE use the group of non-selected individuals as second parent
BGLR.bve
If TRUE use BGLR to perform breeding value estimation
BGLR.model
Select which BGLR model to use (default: "RKHS", alt: "BRR", "BL", "BayesA", "BayesB", "BayesC")
BGLR.burnin
Number of burn-in steps in BGLR (default: 1000)
BGLR.iteration
Number of iterations in BGLR (default: 5000)
BGLR.print
If TRUE set verbose to TRUE in BGLR
copy.individual
If TRUE copy the selected father for a mating
copy.individual.m
If TRUE generate exactly one copy of all selected male in a new cohort (or more by setting breeding.size)
copy.individual.f
If TRUE generate exactly one copy of all selected female in a new cohort (or more by setting breeding.size)
dh.mating
If TRUE generate a DH-line in mating process
dh.sex
Share of DH-lines generated from selected female individuals
n.observation
Number of phenotypes generated per individuals (influences enviromental variance)
bve.0isNA
Individuals with phenotype 0 are used as NA in breeding value estimation
phenotype.bv
If TRUE use phenotype as estimated breeding value
delete.same.origin
If TRUE delete recombination points when genetic origin of adjacent segments is the same
remove.effect.position
If TRUE remove real QTLs in breeding value estimation
estimate.u
If TRUE estimate u in breeding value estimation (Y = Xb + Zu + e)
new.phenotype.correlation
(OLD! - use new.residual.correlation!) Correlation of the simulated enviromental variance
new.residual.correlation
Correlation of the simulated enviromental variance
new.breeding.correlation
Correlation of the simulated genetic variance (child share! heritage is not influenced!)
estimate.add.gen.var
If TRUE estimate additive genetic variance and heritability based on parent model
estimate.pheno.var
If TRUE estimate total variance in breeding value estimation
best1.from.group
(OLD!- use selection.m.database) Groups of individuals to consider as First Parent / Father (also female individuals are possible)
best2.from.group
(OLD!- use selection.f.database) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible)
best1.from.cohort
(OLD!- use selection.m.cohorts) Groups of individuals to consider as First Parent / Father (also female individuals are possible)
best2.from.cohort
(OLD! - use selection.f.cohorts) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible)
add.class.cohorts
Migration levels of all cohorts selected for reproduction are automatically added to class.m/class.f (default: TRUE)
store.comp.times
If TRUE store computation times in $info$comp.times (default: TRUE)
store.comp.times.bve
If TRUE store computation times of breeding value estimation in $info$comp.times.bve (default: TRUE)
store.comp.times.generation
If TRUE store computation times of mating simulations in $info$comp.times.generation (default: TRUE)
import.position.calculation
Function to calculate recombination point into adjacent/following SNP
BGLR.save
Method to use in BGLR (default: "RKHS" - alt: NON currently)
BGLR.save.random
Add random number to store location of internal BGLR computations (only needed when simulating a lot in parallel!)
ogc
If TRUE use optimal genetic contribution theory to perform selection ( This requires the use of the R-package optiSel)
ogc.target
Target of OGC (default: "min.sKin" - minimize inbreeding; alt: "max.BV" / "min.BV" - maximize genetic gain; both under constrains selected below)
ogc.uniform
This corresponds to the uniform constrain in optiSel
ogc.ub
This corresponds to the ub constrain in optiSel
ogc.lb
This corresponds to the lb constrain in optiSel
ogc.ub.sKin
This corresponds to the ub.sKin constrain in optiSel
ogc.lb.BV
This corresponds to the lb.BV constrain in optiSel
ogc.ub.BV
This corresponds to the ub.BV constrain in optiSel
ogc.eq.BV
This corresponds to the eq.BV constrain in optiSel
ogc.ub.sKin.increase
This corresponds to the upper bound (current sKin + ogc.ub.sKin.increase) as ub.sKin in optiSel
ogc.lb.BV.increase
This corresponds to the lower bound (current BV + ogc.lb.BV.increase) as lb.BV in optiSel
emmreml.bve
If TRUE use REML estimator from R-package EMMREML in breeding value estimation
rrblup.bve
If TRUE use REML estimator from R-package rrBLUP in breeding value estimation
sommer.bve
If TRUE use REML estimator from R-package sommer in breeding value estimation
sommer.multi.bve
Set TRUE to use a mulit-trait model in the R-package sommer for BVE
nr.edits
Number of edits to perform per individual
gene.editing.offspring
If TRUE perform gene editing on newly generated individuals
gene.editing.best
If TRUE perform gene editing on selected individuals
gene.editing.offspring.sex
Which sex to perform editing on (Default c(TRUE,TRUE), mw)
gene.editing.best.sex
Which sex to perform editing on (Default c(TRUE,TRUE), mw)
gwas.u
If TRUE estimate u via GWAS (relevant for gene editing)
approx.residuals
If FALSE calculate the variance for each marker separatly instead of using a set variance (doesnt change order - only p-values)
sequenceZ
Split genomic matric into parts (relevent if high memory usage)
maxZ
Number of SNPs to consider in each part of sequenceZ
maxZtotal
Number of matrix entries to consider jointly (maxZ = maxZtotal/number of animals)
delete.sex
Remove all individuals from these sex from generation delete.individuals (default: 1:2 ; note:delete individuals=NULL)
gwas.group.standard
If TRUE standardize phenotypes by group mean
y.gwas.used
What y value to use in GWAS study (Default: "pheno", alt: "bv", "bve")
gen.architecture.m
Genetic architecture for male animal (default: 0 - no transformation)
gen.architecture.f
Genetic architecture for female animal (default: gen.architecture.m - no transformation)
add.architecture
List with two vectors containing (A: length of chromosomes, B: position in cM of SNPs)
ncore
Cores used for parallel computing in compute.snps
ncore.generation
Number of cores to use in parallel generation
Z.integer
If TRUE save Z as a integer in parallel computing
store.effect.freq
If TRUE store the allele frequency of effect markers per generation
backend
Chose the used backend (default: "doParallel", alt: "doMPI")
randomSeed
Set random seed of the process
randomSeed.generation
Set random seed for parallel generation process
Rprof
Store computation times of each function
miraculix
If TRUE use miraculix to perform computations (ideally already generate population in creating.diploid with this; default: automatic detection from population list)
miraculix.cores
Number of cores used in miraculix applications (default: 1)
miraculix.mult
If TRUE use miraculix for matrix multiplications even if miraculix is not used for storage
miraculix.chol
Set to FALSE to deactive miraculix based Cholesky-decomposition (default: TRUE)
best.selection.ratio.m
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1)
best.selection.ratio.f
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1)
best.selection.criteria.m
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno")
best.selection.criteria.f
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno")
best.selection.manual.ratio.m
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7))
best.selection.manual.ratio.f
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7))
best.selection.manual.reorder
Set to FALSE to not use the order from best to worst selected individual but plain order based on database-order
bve.class
Consider only animals of those class classes in breeding value estimation (default: NULL - use all)
parallel.generation
Set TRUE to active parallel computing in animal generation
name.cohort
Name of the newly added cohort
display.progress
Set FALSE to not display progress bars. Setting verbose to FALSE will automatically deactive progress bars
combine
Copy existing individuals (e.g. to merge individuals from different groups in a joined cohort). Individuals to use are used as the first parent
repeat.mating
Generate multiple mating from the same dam/sire combination (first column: number of offspring; second column: probability)
repeat.mating.copy
Generate multiple copies from a copy action (combine / copy.individuals.m/f) (first column: number of offspring; second column: probability)
repeat.mating.fixed
Vector containing number of times each mating is repeated. This will overwrite sampling from repeat.mating / repeat.mating.copy (default: NULL)
repeat.mating.overwrite
Set to FALSE to not use the current repeat.mating / repeat.mating.copy input as the new standard values (default: TRUE)
time.point
Time point at which the new individuals are generated
creating.type
Technique to generate new individuals (usage in web-based application)
multiple.observation
Set TRUE to allow for more than one phenotype observation per individual (this will decrease enviromental variance!)
new.bv.observation
(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")
new.bv.observation.gen
(OLD! use phenotyping.gen) Vector of generation from which to generate additional phenotypes
new.bv.observation.cohorts
(OLD! use phenotyping.cohorts)Vector of cohorts from which to generate additional phenotype
new.bv.observation.database
(OLD! use phenotyping.database) Matrix of groups from which to generate additional phenotypes
phenotyping
Quick acces to phenotyping for (all: "all", non-phenotyped: "non_obs", non-phenotyped male: "non_obs_m", non-phenotyped female: "non_obs_f")
phenotyping.gen
Vector of generation from which to generate additional phenotypes
phenotyping.cohorts
Vector of cohorts from which to generate additional phenotype
phenotyping.database
Matrix of groups from which to generate additional phenotypes
bve.gen
Generations of individuals to consider in breeding value estimation (default: NULL)
bve.cohorts
Cohorts of individuals to consider in breeding value estimation (default: NULL)
bve.database
Groups of individuals to consider in breeding value estimation (default: NULL)
sigma.e.gen
Generations to consider when estimating sigma.e when using hertability
sigma.e.cohorts
Cohorts to consider when estimating sigma.e when using hertability
sigma.e.database
Groups to consider when estimating sigma.e when using hertability
sigma.g.gen
Generations to consider when estimating sigma.g
sigma.g.cohorts
Cohorts to consider when estimating sigma.g
sigma.g.database
Groups to consider when estimating sigma.g
gwas.gen
Generations to consider in GWAS analysis
gwas.cohorts
Cohorts to consider in GWAS analysis
gwas.database
Groups to consider in GWAS analysis
bve.insert.gen
Generations of individuals to compute breeding values for (default: all groups in bve.database)
bve.insert.cohorts
Cohorts of individuals to compute breeding values for (default: all groups in bve.database)
bve.insert.database
Groups of individuals to compute breeding values for (default: all groups in bve.database)
reduced.selection.panel.m
Use only a subset of individuals of the potential selected ones ("Split in user-interface")
reduced.selection.panel.f
Use only a subset of individuals of the potential selected ones ("Split in user-interface")
breeding.all.combination
Set to TRUE to automatically perform each mating combination possible exactly ones.
depth.pedigree
Depth of the pedigree in generations (default: 7)
depth.pedigree.ogc
Depth of the pedigree in generations (default: 7)
copy.individual.keep.bve
Set to FALSE to not keep estimated breeding value in case of use of copy.individuals
copy.individual.keep.pheno
Set to FALSE to not keep estimated breeding values in case of use of copy.individuals
bve.avoid.duplicates
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.accuracy
Report the accuracy of the breeding value estimation
share.genotyped
Share of individuals newly generated individuals that are genotyped
singlestep.active
Set TRUE to use single step in breeding value estimation (only implemented for vanRaden- G matrix and without use sequenceZ) (Legarra 2014)
remove.non.genotyped
Set to FALSE to manually include non-genotyped individuals in genetic BVE, single-step will deactive this as well
added.genotyped
Share of individuals that is additionally genotyped (only for copy.individuals)
fast.uhat
Set to FALSE to derive inverse of A in rrBLUP
offspring.bve.parents.gen
Generations to consider to derive phenotype from offspring phenotypes
offspring.bve.parents.database
Groups to consider to derive phenotype from offspring phenotypes
offspring.bve.parents.cohorts
Cohorts to consider to derive phenotype from offspring phenotypes
offspring.bve.offspring.gen
Active generations for import of offspring phenotypes
offspring.bve.offspring.database
Active groups for import of offspring phenotypes
offspring.bve.offspring.cohorts
Active cohorts for import of offspring phenotypes
culling.gen
Generations to consider to culling
culling.database
Groups to consider to culling
culling.cohort
Cohort to consider to culling
culling.time
Age of the individuals at culling
culling.name
Name of the culling action (user-interface stuff)
culling.bv1
Reference Breeding value
culling.share1
Probability of death for individuals with bv1
culling.bv2
Alternative breeding value (linear extended for other bvs)
culling.share2
Probability of death for individuals with bv2
culling.index
Genomic index (default:0 - no genomic impact, use: "lastindex" to use the last selection index applied in selection)
culling.single
Set to FALSE to not apply the culling module on all individuals of the cohort
culling.all.copy
Set to FALSE to not kill copies of the same individual in the culling module
calculate.reliability
Set TRUE to calculate a reliability when performing Direct-Mixed-Model BVE
selection.m.gen
Generations available for selection of paternal parent
selection.f.gen
Generations available for selection of maternal parent
selection.m.database
Groups available for selection of paternal parent
selection.f.database
Groups available for selection of maternal parent
selection.m.cohorts
Cohorts available for selection of paternal parent
selection.f.cohorts
Cohorts available for selection of maternal parent
selection.m.miesenberger
Use Weighted selection index according to Miesenberger 1997 for paternal selection
selection.f.miesenberger
Use Weighted selection index according to Miesenberger 1997 for maternal selection
selection.miesenberger.reliability.est
If available reliability estimated are used. If not use default:"estimated" (SD BVE / SD Pheno), alt: "heritability", "derived" (cor(BVE,BV)^2) as replacement
miesenberger.trafo
Ignore all eigenvalues below this threshold and apply dimension reduction (default: 0 - use all)
multiple.bve.weights.m
Weighting between traits when using "add" (default: 1)
multiple.bve.weights.f
Weighting between traits when using "add" (default: same as multiple.bve.weights.m)
multiple.bve.scale.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
multiple.bve.scale.f
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
verbose
Set to FALSE to not display any prints
bve.parent.mean
Set to TRUE to use the average parental performance as the breeding value estimate
bve.grandparent.mean
Set to TRUE to use the average grandparental performance as the breeding value estimate
bve.mean.between
Select if you want to use the "bve", "bv", "pheno" or "bvepheno" to form the mean (default: "bvepheno" - if available bve, else pheno)
bve.direct.est
If TRUE predict BVEs in direct estimation according to vanRaden 2008 method 2 (default: TRUE)
bve.pseudo
If set to TRUE the breeding value estimation will be simulated with resulting accuracy bve.pseudo.accuracy (default: 1)
bve.pseudo.accuracy
The accuracy to be obtained in the "pseudo" - breeding value estimation
miraculix.destroyA
If FALSE A will not be destroyed in the process of inversion (less computing / more memory)
mas.bve
If TRUE use marker assisted selection in the breeding value estimation
mas.markers
Vector containing markers to be used in marker assisted selection
mas.number
If no markers are provided this nr of markers is selected (if single marker QTL are present highest effect markers are prioritized)
mas.effects
Effects assigned to the MAS markers (Default: estimated via lm())
threshold.selection
Minimum value in the selection index selected individuals have to have
threshold.sign
Pick all individuals above (">") the threshold. Alt: ("<", "=", "<=", ">=")
input.phenotype
Select what to use in BVE (default: own phenotype ("own"), offspring phenotype ("off"), their average ("mean") or a weighted average ("weighted"))
bve.ignore.traits
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)
bv.ignore.traits
Vector of traits to ignore in the calculation of the genomic value (default: NULL; Only recommended for high number of traits and experienced users!)
genotyped.database
Groups to generate genotype data (that can be used in a BVE)
genotyped.gen
Generations to generate genotype data (that can be used in a BVE)
genotyped.cohorts
Cohorts to generate genotype data (that can be used in a BVE)
genotyped.share
Share of individuals in genotyped.gen/database/cohort to generate genotype data from (default: 1)
genotyped.array
Genotyping array used
sex.s
Specify which newly added individuals are male (1) or female (2)
bve.imputation
Set to FALSE to not perform imputation up to the highest marker density of genotyping data that is available
bve.imputation.errorrate
Share of errors in the imputation procedure (default: 0)
share.phenotyped
Share of the individuals to phenotype
avoid.mating.fullsib
Set to TRUE to not generate offspring of full siblings
avoid.mating.halfsib
Set to TRUE to not generate offspring from half or full siblings
max.mating.pair
Set to the maximum number of matings between two individuals (default: Inf)
bve.per.sample.sigma.e
Set to FALSE to deactivate the use of a heritablity based on the number of observations generated per sample
bve.solve
Provide solver to be used in BVE (default: "exact" solution via inversion, alt: "pcg", function with inputs A, b and output y_hat)
Value
Population-list
Examples
1
2
population <- creating.diploid(nsnp=1000, nindi=100)
population <- breeding.diploid(population, breeding.size=100, selection.size=c(25,25))
MoBPS documentation built on Nov. 9, 2021, 5:08 p.m.
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Description Usage Arguments Value Examples
View source: R/breeding.diploid.R
Description
Function to simulate a step in a breeding scheme
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 | 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"
)
|
Arguments
population |
Population list |
mutation.rate |
Mutation rate in each marker (default: 10^-8) |
remutation.rate |
Remutation rate in each marker (default: 10^-8) |
recombination.rate |
Average number of recombination per 1 length unit (default: 1M) |
selection.m |
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.f |
Selection criteria for female individuals (default: selection.m , alt: "random", function") |
new.selection.calculation |
If TRUE recalculate breeding values obtained by selection.function.matrix |
selection.function.matrix |
Manuel generation of a temporary selection function (Use BVs instead!) |
selection.size |
Number of selected individuals for breeding (default: c(0,0) - alt: positive numbers) |
ignore.best |
Not consider the top individuals of the selected individuals (e.g. to use 2-10 best individuals) |
breeding.size |
Number of individuals to generate |
breeding.sex |
Share of female animals (if single value is used for breeding size; default: 0.5) |
breeding.sex.random |
If TRUE randomly chose sex of new individuals (default: FALSE - use expected values) |
relative.selection |
Use best.selection.ratio instead! |
class.m |
Migrationlevels of male individuals to consider for mating process (default: 0) |
class.f |
Migrationlevels of female individuals to consider for mating process (default: 0) |
add.gen |
Generation you want to add the new individuals to (default: New generation) |
recom.f.indicator |
Use step function for recombination map (transform snp.positions if possible instead) |
duplication.rate |
Share of recombination points with a duplication (default: 0 - DEACTIVATED) |
duplication.length |
Average length of a duplication (Exponentially distributed) |
duplication.recombination |
Average number of recombinations per 1 length uit of duplication (default: 1) |
new.class |
Migration level of newly generated individuals (default: 0) |
bve |
If TRUE perform a breeding value estimation (default: FALSE) |
sigma.e |
Enviromental variance (default: 100) |
sigma.g |
Genetic variance (default: 100 - only used if not computed via estimate.sigma.g^2 in der Zuchtwertschaetzung (Default: 100) |
new.bv.child |
(OLD! - use phenotyping.child) Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0) |
phenotyping.child |
Starting phenotypes of newly generated individuals (default: "mean" of both parents, "obs" - regular observation, "zero" - 0) |
relationship.matrix |
Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM") |
relationship.matrix.ogc |
Method to calculate relationship matrix for OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM") |
computation.A |
(OLD! - use relationship.matrix) Method to calculate relationship matrix for the breeding value estimation (Default: "vanRaden", alt: "kinship", "CE", "non_stand", "CE2", "CM") |
computation.A.ogc |
(OLD! use relationship.matrix.ogc) Method to calculate pedigree matrix in OGC (Default: "kinship", alt: "vanRaden", "CE", "non_stand", "CE2", "CM") |
delete.haplotypes |
Generations for with haplotypes of founders can be deleted (only use if storage problem!) |
delete.individuals |
Generations for with individuals are completley deleted (only use if storage problem!) |
fixed.breeding |
Set of targeted matings to perform |
fixed.breeding.best |
Perform targeted matings in the group of selected individuals |
max.offspring |
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w)) |
max.litter |
Maximum number of offspring per individual (default: c(Inf,Inf) - (m,w)) |
store.breeding.totals |
If TRUE store information on selected animals in $info$breeding.totals |
forecast.sigma.g |
Set FALSE to not estimate sigma.g (Default: TRUE) |
multiple.bve |
Way to handle multiple traits in bv/selection (default: "add", alt: "ranking") |
store.bve.data |
If TRUE store information of bve in $info$bve.data |
fixed.assignment |
Set TRUE for targeted mating of best-best individual till worst-worst (of selected). set to "bestworst" for best-worst mating |
reduce.group |
(OLD! - use culling modules) Groups of animals for reduce to a new size (by changing class to -1) |
reduce.group.selection |
(OLD! - use culling modules) Selection criteria for reduction of groups (cf. selection.m / selection.f - default: "random") |
selection.highest |
If 0 individuals with lowest bve are selected as best individuals (default c(1,1) - (m,w)) |
selection.criteria |
What to use in the selection proces (default: "bve", alt: "bv", "pheno") |
same.sex.activ |
If TRUE allow matings of individuals of same sex |
same.sex.sex |
Probability to use female individuals as parents (default: 0.5) |
same.sex.selfing |
Set to TRUE to allow for selfing when using same.sex matings |
selfing.mating |
If TRUE generate new individuals via selfing |
selfing.sex |
Share of female individuals used for selfing (default: 0.5) |
praeimplantation |
Only use matings the lead to a specific genotype in a specific marker |
heritability |
Use sigma.e to obtain a certain heritability (default: NULL) |
repeatability |
Set this to control the share of the residual variance (sigma.e) that is permanent (there for each observation) |
save.recombination.history |
If TRUE store the time point of each recombination event |
martini.selection |
If TRUE use the group of non-selected individuals as second parent |
BGLR.bve |
If TRUE use BGLR to perform breeding value estimation |
BGLR.model |
Select which BGLR model to use (default: "RKHS", alt: "BRR", "BL", "BayesA", "BayesB", "BayesC") |
BGLR.burnin |
Number of burn-in steps in BGLR (default: 1000) |
BGLR.iteration |
Number of iterations in BGLR (default: 5000) |
BGLR.print |
If TRUE set verbose to TRUE in BGLR |
copy.individual |
If TRUE copy the selected father for a mating |
copy.individual.m |
If TRUE generate exactly one copy of all selected male in a new cohort (or more by setting breeding.size) |
copy.individual.f |
If TRUE generate exactly one copy of all selected female in a new cohort (or more by setting breeding.size) |
dh.mating |
If TRUE generate a DH-line in mating process |
dh.sex |
Share of DH-lines generated from selected female individuals |
n.observation |
Number of phenotypes generated per individuals (influences enviromental variance) |
bve.0isNA |
Individuals with phenotype 0 are used as NA in breeding value estimation |
phenotype.bv |
If TRUE use phenotype as estimated breeding value |
delete.same.origin |
If TRUE delete recombination points when genetic origin of adjacent segments is the same |
remove.effect.position |
If TRUE remove real QTLs in breeding value estimation |
estimate.u |
If TRUE estimate u in breeding value estimation (Y = Xb + Zu + e) |
new.phenotype.correlation |
(OLD! - use new.residual.correlation!) Correlation of the simulated enviromental variance |
new.residual.correlation |
Correlation of the simulated enviromental variance |
new.breeding.correlation |
Correlation of the simulated genetic variance (child share! heritage is not influenced!) |
estimate.add.gen.var |
If TRUE estimate additive genetic variance and heritability based on parent model |
estimate.pheno.var |
If TRUE estimate total variance in breeding value estimation |
best1.from.group |
(OLD!- use selection.m.database) Groups of individuals to consider as First Parent / Father (also female individuals are possible) |
best2.from.group |
(OLD!- use selection.f.database) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible) |
best1.from.cohort |
(OLD!- use selection.m.cohorts) Groups of individuals to consider as First Parent / Father (also female individuals are possible) |
best2.from.cohort |
(OLD! - use selection.f.cohorts) Groups of individuals to consider as Second Parent / Mother (also male individuals are possible) |
add.class.cohorts |
Migration levels of all cohorts selected for reproduction are automatically added to class.m/class.f (default: TRUE) |
store.comp.times |
If TRUE store computation times in $info$comp.times (default: TRUE) |
store.comp.times.bve |
If TRUE store computation times of breeding value estimation in $info$comp.times.bve (default: TRUE) |
store.comp.times.generation |
If TRUE store computation times of mating simulations in $info$comp.times.generation (default: TRUE) |
import.position.calculation |
Function to calculate recombination point into adjacent/following SNP |
BGLR.save |
Method to use in BGLR (default: "RKHS" - alt: NON currently) |
BGLR.save.random |
Add random number to store location of internal BGLR computations (only needed when simulating a lot in parallel!) |
ogc |
If TRUE use optimal genetic contribution theory to perform selection ( This requires the use of the R-package optiSel) |
ogc.target |
Target of OGC (default: "min.sKin" - minimize inbreeding; alt: "max.BV" / "min.BV" - maximize genetic gain; both under constrains selected below) |
ogc.uniform |
This corresponds to the uniform constrain in optiSel |
ogc.ub |
This corresponds to the ub constrain in optiSel |
ogc.lb |
This corresponds to the lb constrain in optiSel |
ogc.ub.sKin |
This corresponds to the ub.sKin constrain in optiSel |
ogc.lb.BV |
This corresponds to the lb.BV constrain in optiSel |
ogc.ub.BV |
This corresponds to the ub.BV constrain in optiSel |
ogc.eq.BV |
This corresponds to the eq.BV constrain in optiSel |
ogc.ub.sKin.increase |
This corresponds to the upper bound (current sKin + ogc.ub.sKin.increase) as ub.sKin in optiSel |
ogc.lb.BV.increase |
This corresponds to the lower bound (current BV + ogc.lb.BV.increase) as lb.BV in optiSel |
emmreml.bve |
If TRUE use REML estimator from R-package EMMREML in breeding value estimation |
rrblup.bve |
If TRUE use REML estimator from R-package rrBLUP in breeding value estimation |
sommer.bve |
If TRUE use REML estimator from R-package sommer in breeding value estimation |
sommer.multi.bve |
Set TRUE to use a mulit-trait model in the R-package sommer for BVE |
nr.edits |
Number of edits to perform per individual |
gene.editing.offspring |
If TRUE perform gene editing on newly generated individuals |
gene.editing.best |
If TRUE perform gene editing on selected individuals |
gene.editing.offspring.sex |
Which sex to perform editing on (Default c(TRUE,TRUE), mw) |
gene.editing.best.sex |
Which sex to perform editing on (Default c(TRUE,TRUE), mw) |
gwas.u |
If TRUE estimate u via GWAS (relevant for gene editing) |
approx.residuals |
If FALSE calculate the variance for each marker separatly instead of using a set variance (doesnt change order - only p-values) |
sequenceZ |
Split genomic matric into parts (relevent if high memory usage) |
maxZ |
Number of SNPs to consider in each part of sequenceZ |
maxZtotal |
Number of matrix entries to consider jointly (maxZ = maxZtotal/number of animals) |
delete.sex |
Remove all individuals from these sex from generation delete.individuals (default: 1:2 ; note:delete individuals=NULL) |
gwas.group.standard |
If TRUE standardize phenotypes by group mean |
y.gwas.used |
What y value to use in GWAS study (Default: "pheno", alt: "bv", "bve") |
gen.architecture.m |
Genetic architecture for male animal (default: 0 - no transformation) |
gen.architecture.f |
Genetic architecture for female animal (default: gen.architecture.m - no transformation) |
add.architecture |
List with two vectors containing (A: length of chromosomes, B: position in cM of SNPs) |
ncore |
Cores used for parallel computing in compute.snps |
ncore.generation |
Number of cores to use in parallel generation |
Z.integer |
If TRUE save Z as a integer in parallel computing |
store.effect.freq |
If TRUE store the allele frequency of effect markers per generation |
backend |
Chose the used backend (default: "doParallel", alt: "doMPI") |
randomSeed |
Set random seed of the process |
randomSeed.generation |
Set random seed for parallel generation process |
Rprof |
Store computation times of each function |
miraculix |
If TRUE use miraculix to perform computations (ideally already generate population in creating.diploid with this; default: automatic detection from population list) |
miraculix.cores |
Number of cores used in miraculix applications (default: 1) |
miraculix.mult |
If TRUE use miraculix for matrix multiplications even if miraculix is not used for storage |
miraculix.chol |
Set to FALSE to deactive miraculix based Cholesky-decomposition (default: TRUE) |
best.selection.ratio.m |
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1) |
best.selection.ratio.f |
Ratio of the frequency of the selection of the best best animal and the worst best animal (default=1) |
best.selection.criteria.m |
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno") |
best.selection.criteria.f |
Criteria to calculate this ratio (default: "bv", alt: "bve", "pheno") |
best.selection.manual.ratio.m |
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7)) |
best.selection.manual.ratio.f |
vector containing probability to draw from for every individual (e.g. c(0.1,0.2,0.7)) |
best.selection.manual.reorder |
Set to FALSE to not use the order from best to worst selected individual but plain order based on database-order |
bve.class |
Consider only animals of those class classes in breeding value estimation (default: NULL - use all) |
parallel.generation |
Set TRUE to active parallel computing in animal generation |
name.cohort |
Name of the newly added cohort |
display.progress |
Set FALSE to not display progress bars. Setting verbose to FALSE will automatically deactive progress bars |
combine |
Copy existing individuals (e.g. to merge individuals from different groups in a joined cohort). Individuals to use are used as the first parent |
repeat.mating |
Generate multiple mating from the same dam/sire combination (first column: number of offspring; second column: probability) |
repeat.mating.copy |
Generate multiple copies from a copy action (combine / copy.individuals.m/f) (first column: number of offspring; second column: probability) |
repeat.mating.fixed |
Vector containing number of times each mating is repeated. This will overwrite sampling from repeat.mating / repeat.mating.copy (default: NULL) |
repeat.mating.overwrite |
Set to FALSE to not use the current repeat.mating / repeat.mating.copy input as the new standard values (default: TRUE) |
time.point |
Time point at which the new individuals are generated |
creating.type |
Technique to generate new individuals (usage in web-based application) |
multiple.observation |
Set TRUE to allow for more than one phenotype observation per individual (this will decrease enviromental variance!) |
new.bv.observation |
(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") |
new.bv.observation.gen |
(OLD! use phenotyping.gen) Vector of generation from which to generate additional phenotypes |
new.bv.observation.cohorts |
(OLD! use phenotyping.cohorts)Vector of cohorts from which to generate additional phenotype |
new.bv.observation.database |
(OLD! use phenotyping.database) Matrix of groups from which to generate additional phenotypes |
phenotyping |
Quick acces to phenotyping for (all: "all", non-phenotyped: "non_obs", non-phenotyped male: "non_obs_m", non-phenotyped female: "non_obs_f") |
phenotyping.gen |
Vector of generation from which to generate additional phenotypes |
phenotyping.cohorts |
Vector of cohorts from which to generate additional phenotype |
phenotyping.database |
Matrix of groups from which to generate additional phenotypes |
bve.gen |
Generations of individuals to consider in breeding value estimation (default: NULL) |
bve.cohorts |
Cohorts of individuals to consider in breeding value estimation (default: NULL) |
bve.database |
Groups of individuals to consider in breeding value estimation (default: NULL) |
sigma.e.gen |
Generations to consider when estimating sigma.e when using hertability |
sigma.e.cohorts |
Cohorts to consider when estimating sigma.e when using hertability |
sigma.e.database |
Groups to consider when estimating sigma.e when using hertability |
sigma.g.gen |
Generations to consider when estimating sigma.g |
sigma.g.cohorts |
Cohorts to consider when estimating sigma.g |
sigma.g.database |
Groups to consider when estimating sigma.g |
gwas.gen |
Generations to consider in GWAS analysis |
gwas.cohorts |
Cohorts to consider in GWAS analysis |
gwas.database |
Groups to consider in GWAS analysis |
bve.insert.gen |
Generations of individuals to compute breeding values for (default: all groups in bve.database) |
bve.insert.cohorts |
Cohorts of individuals to compute breeding values for (default: all groups in bve.database) |
bve.insert.database |
Groups of individuals to compute breeding values for (default: all groups in bve.database) |
reduced.selection.panel.m |
Use only a subset of individuals of the potential selected ones ("Split in user-interface") |
reduced.selection.panel.f |
Use only a subset of individuals of the potential selected ones ("Split in user-interface") |
breeding.all.combination |
Set to TRUE to automatically perform each mating combination possible exactly ones. |
depth.pedigree |
Depth of the pedigree in generations (default: 7) |
depth.pedigree.ogc |
Depth of the pedigree in generations (default: 7) |
copy.individual.keep.bve |
Set to FALSE to not keep estimated breeding value in case of use of copy.individuals |
copy.individual.keep.pheno |
Set to FALSE to not keep estimated breeding values in case of use of copy.individuals |
bve.avoid.duplicates |
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.accuracy |
Report the accuracy of the breeding value estimation |
share.genotyped |
Share of individuals newly generated individuals that are genotyped |
singlestep.active |
Set TRUE to use single step in breeding value estimation (only implemented for vanRaden- G matrix and without use sequenceZ) (Legarra 2014) |
remove.non.genotyped |
Set to FALSE to manually include non-genotyped individuals in genetic BVE, single-step will deactive this as well |
added.genotyped |
Share of individuals that is additionally genotyped (only for copy.individuals) |
fast.uhat |
Set to FALSE to derive inverse of A in rrBLUP |
offspring.bve.parents.gen |
Generations to consider to derive phenotype from offspring phenotypes |
offspring.bve.parents.database |
Groups to consider to derive phenotype from offspring phenotypes |
offspring.bve.parents.cohorts |
Cohorts to consider to derive phenotype from offspring phenotypes |
offspring.bve.offspring.gen |
Active generations for import of offspring phenotypes |
offspring.bve.offspring.database |
Active groups for import of offspring phenotypes |
offspring.bve.offspring.cohorts |
Active cohorts for import of offspring phenotypes |
culling.gen |
Generations to consider to culling |
culling.database |
Groups to consider to culling |
culling.cohort |
Cohort to consider to culling |
culling.time |
Age of the individuals at culling |
culling.name |
Name of the culling action (user-interface stuff) |
culling.bv1 |
Reference Breeding value |
culling.share1 |
Probability of death for individuals with bv1 |
culling.bv2 |
Alternative breeding value (linear extended for other bvs) |
culling.share2 |
Probability of death for individuals with bv2 |
culling.index |
Genomic index (default:0 - no genomic impact, use: "lastindex" to use the last selection index applied in selection) |
culling.single |
Set to FALSE to not apply the culling module on all individuals of the cohort |
culling.all.copy |
Set to FALSE to not kill copies of the same individual in the culling module |
calculate.reliability |
Set TRUE to calculate a reliability when performing Direct-Mixed-Model BVE |
selection.m.gen |
Generations available for selection of paternal parent |
selection.f.gen |
Generations available for selection of maternal parent |
selection.m.database |
Groups available for selection of paternal parent |
selection.f.database |
Groups available for selection of maternal parent |
selection.m.cohorts |
Cohorts available for selection of paternal parent |
selection.f.cohorts |
Cohorts available for selection of maternal parent |
selection.m.miesenberger |
Use Weighted selection index according to Miesenberger 1997 for paternal selection |
selection.f.miesenberger |
Use Weighted selection index according to Miesenberger 1997 for maternal selection |
selection.miesenberger.reliability.est |
If available reliability estimated are used. If not use default:"estimated" (SD BVE / SD Pheno), alt: "heritability", "derived" (cor(BVE,BV)^2) as replacement |
miesenberger.trafo |
Ignore all eigenvalues below this threshold and apply dimension reduction (default: 0 - use all) |
multiple.bve.weights.m |
Weighting between traits when using "add" (default: 1) |
multiple.bve.weights.f |
Weighting between traits when using "add" (default: same as multiple.bve.weights.m) |
multiple.bve.scale.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 |
multiple.bve.scale.f |
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 |
verbose |
Set to FALSE to not display any prints |
bve.parent.mean |
Set to TRUE to use the average parental performance as the breeding value estimate |
bve.grandparent.mean |
Set to TRUE to use the average grandparental performance as the breeding value estimate |
bve.mean.between |
Select if you want to use the "bve", "bv", "pheno" or "bvepheno" to form the mean (default: "bvepheno" - if available bve, else pheno) |
bve.direct.est |
If TRUE predict BVEs in direct estimation according to vanRaden 2008 method 2 (default: TRUE) |
bve.pseudo |
If set to TRUE the breeding value estimation will be simulated with resulting accuracy bve.pseudo.accuracy (default: 1) |
bve.pseudo.accuracy |
The accuracy to be obtained in the "pseudo" - breeding value estimation |
miraculix.destroyA |
If FALSE A will not be destroyed in the process of inversion (less computing / more memory) |
mas.bve |
If TRUE use marker assisted selection in the breeding value estimation |
mas.markers |
Vector containing markers to be used in marker assisted selection |
mas.number |
If no markers are provided this nr of markers is selected (if single marker QTL are present highest effect markers are prioritized) |
mas.effects |
Effects assigned to the MAS markers (Default: estimated via lm()) |
threshold.selection |
Minimum value in the selection index selected individuals have to have |
threshold.sign |
Pick all individuals above (">") the threshold. Alt: ("<", "=", "<=", ">=") |
input.phenotype |
Select what to use in BVE (default: own phenotype ("own"), offspring phenotype ("off"), their average ("mean") or a weighted average ("weighted")) |
bve.ignore.traits |
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) |
bv.ignore.traits |
Vector of traits to ignore in the calculation of the genomic value (default: NULL; Only recommended for high number of traits and experienced users!) |
genotyped.database |
Groups to generate genotype data (that can be used in a BVE) |
genotyped.gen |
Generations to generate genotype data (that can be used in a BVE) |
genotyped.cohorts |
Cohorts to generate genotype data (that can be used in a BVE) |
genotyped.share |
Share of individuals in genotyped.gen/database/cohort to generate genotype data from (default: 1) |
genotyped.array |
Genotyping array used |
sex.s |
Specify which newly added individuals are male (1) or female (2) |
bve.imputation |
Set to FALSE to not perform imputation up to the highest marker density of genotyping data that is available |
bve.imputation.errorrate |
Share of errors in the imputation procedure (default: 0) |
share.phenotyped |
Share of the individuals to phenotype |
avoid.mating.fullsib |
Set to TRUE to not generate offspring of full siblings |
avoid.mating.halfsib |
Set to TRUE to not generate offspring from half or full siblings |
max.mating.pair |
Set to the maximum number of matings between two individuals (default: Inf) |
bve.per.sample.sigma.e |
Set to FALSE to deactivate the use of a heritablity based on the number of observations generated per sample |
bve.solve |
Provide solver to be used in BVE (default: "exact" solution via inversion, alt: "pcg", function with inputs A, b and output y_hat) |
Value
Population-list
Examples
1 2 | population <- creating.diploid(nsnp=1000, nindi=100)
population <- breeding.diploid(population, breeding.size=100, selection.size=c(25,25))
|
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