creating.trait {MoBPS}

Generation of genomic traits

Description

Generation of the trait in a starting population

Usage

creating.trait(
  population,
  real.bv.add = NULL,
  real.bv.mult = NULL,
  real.bv.dice = NULL,
  bv.total = 0,
  polygenic.variance = 100,
  bve.mult.factor = NULL,
  bve.poly.factor = NULL,
  base.bv = NULL,
  new.phenotype.correlation = NULL,
  new.residual.correlation = NULL,
  new.breeding.correlation = NULL,
  n.additive = 0,
  n.equal.additive = 0,
  n.dominant = 0,
  n.equal.dominant = 0,
  n.qualitative = 0,
  n.quantitative = 0,
  dominant.only.positive = FALSE,
  var.additive.l = NULL,
  var.dominant.l = NULL,
  var.qualitative.l = NULL,
  var.quantitative.l = NULL,
  effect.size.equal.add = 1,
  effect.size.equal.dom = 1,
  exclude.snps = NULL,
  randomSeed = NULL,
  shuffle.traits = NULL,
  shuffle.cor = NULL,
  replace.traits = FALSE,
  trait.name = NULL,
  remove.invalid.qtl = TRUE,
  bv.standard = FALSE,
  mean.target = NULL,
  var.target = NULL,
  verbose = TRUE,
  is.maternal = NULL,
  is.paternal = NULL
)

Arguments

population

Population list

real.bv.add

Single Marker effects

real.bv.mult

Two Marker effects

real.bv.dice

Multi-marker effects

bv.total

Number of traits (If more than traits via real.bv.X use traits with no directly underlying QTL)

polygenic.variance

Genetic variance of traits with no underlying QTL

bve.mult.factor

Multiplicate trait value times this

bve.poly.factor

Potency trait value over this

base.bv

Average genetic value of a trait

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!

n.additive

Number of additive QTL with effect size drawn from a gaussian distribution

n.equal.additive

Number of additive QTL with equal effect size (effect.size)

n.dominant

Number of dominant QTL with effect size drawn from a gaussian distribution

n.equal.dominant

Number of n.equal.dominant QTL with equal effect size

n.qualitative

Number of qualitative epistatic QTL

n.quantitative

Number of quantitative epistatic QTL

dominant.only.positive

Set to TRUE to always asign the heterozygous variant with the higher of the two homozygous effects (e.g. hybrid breeding); default: FALSE

var.additive.l

Variance of additive QTL

var.dominant.l

Variance of dominante QTL

var.qualitative.l

Variance of qualitative epistatic QTL

var.quantitative.l

Variance of quantitative epistatic QTL

effect.size.equal.add

Effect size of the QTLs in n.equal.additive

effect.size.equal.dom

Effect size of the QTLs in n.equal.dominant

exclude.snps

Marker were no QTL are simulated on

randomSeed

Set random seed of the process

shuffle.traits

Combine different traits into a joined trait

shuffle.cor

Target Correlation between shuffeled traits

replace.traits

If TRUE delete the simulated traits added before

trait.name

Name of the trait generated

remove.invalid.qtl

Set to FALSE to deactive the automatic removal of QTLs on markers that do not exist

bv.standard

Set TRUE to standardize trait mean and variance via bv.standardization()

mean.target

Target mean

var.target

Target variance

verbose

Set to FALSE to not display any prints

is.maternal

Vector coding if a trait is caused by a maternal effect (Default: all FALSE)

is.paternal

Vector coding if a trait is caused by a paternal effect (Default: all FALSE)

Value

Population-list with one or more additional new traits

Examples

population <- creating.diploid(nsnp=1000, nindi=100)
population <- creating.trait(population, n.additive=100)