breeding.diploid {MoBPS}

Breeding function

Description

Function to simulate a step in a breeding scheme

Usage

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

population <- creating.diploid(nsnp=1000, nindi=100)
population <- breeding.diploid(population, breeding.size=100, selection.size=c(25,25))