creating.diploid: Generation of the starting population

In MoBPS: Modular Breeding Program Simulator

Generation of the starting population

Description

Generation of the starting population

Usage

creating.diploid(
  population = NULL,
  nsnp = 0,
  nindi = 0,
  nqtl = 0,
  name.cohort = NULL,
  generation = 1,
  founder.pool = 1,
  one.sex.mode = FALSE,
  database.sex.mode = FALSE,
  sex.s = "fixed",
  sex.quota = 0.5,
  class = 0L,
  verbose = TRUE,
  map = NULL,
  chr.nr = NULL,
  chromosome.length = NULL,
  bp = NULL,
  snps.equidistant = NULL,
  template.chip = NULL,
  snp.position = NULL,
  change.order = TRUE,
  add.chromosome = FALSE,
  bpcm.conversion = 0,
  snp.name = NULL,
  hom0 = NULL,
  hom1 = NULL,
  dataset = NULL,
  freq = "beta",
  beta.shape1 = 1,
  beta.shape2 = 1,
  share.genotyped = 0,
  genotyped.s = NULL,
  vcf = NULL,
  vcf.maxsnp = Inf,
  vcf.maxindi = Inf,
  vcf.chromosomes = NULL,
  vcf.VA = TRUE,
  trait.name = NULL,
  mean.target = NULL,
  var.target = NULL,
  qtl.position.shared = FALSE,
  trait.cor = NULL,
  trait.cor.include = NULL,
  n.additive = 0,
  n.equal.additive = 0,
  n.dominant = 0,
  n.equal.dominant = 0,
  n.overdominant = 0,
  n.equal.overdominant = 0,
  n.qualitative = 0,
  n.quantitative = 0,
  effect.distribution = "gauss",
  gamma.shape1 = 1,
  gamma.shape2 = 1,
  real.bv.add = NULL,
  real.bv.mult = NULL,
  real.bv.dice = NULL,
  new.residual.correlation = NULL,
  new.breeding.correlation = NULL,
  litter.effect.covariance = NULL,
  pen.effect.covariance = NULL,
  is.maternal = NULL,
  is.paternal = NULL,
  fixed.effects = NULL,
  trait.pool = 0,
  gxe.correlation = NULL,
  n.locations = NULL,
  gxe.max = 0.85,
  gxe.min = 0.7,
  location.name = NULL,
  gxe.combine = TRUE,
  n.traits = 0,
  base.bv = NULL,
  dominant.only.positive = FALSE,
  exclude.snps = NULL,
  var.additive.l = NULL,
  var.dominant.l = NULL,
  var.overdominant.l = NULL,
  var.qualitative.l = NULL,
  var.quantitative.l = NULL,
  effect.size.equal.add = 1,
  effect.size.equal.dom = 1,
  effect.size.equal.over = 1,
  polygenic.variance = 100,
  bve.mult.factor = NULL,
  bve.poly.factor = NULL,
  set.zero = FALSE,
  bv.standard = FALSE,
  replace.real.bv = FALSE,
  bv.ignore.traits = NULL,
  remove.invalid.qtl = TRUE,
  randomSeed = NULL,
  add.architecture = NULL,
  time.point = 0,
  creating.type = 0,
  size.scaling = 1,
  progress.bar = TRUE,
  miraculix = TRUE,
  miraculix.dataset = TRUE,
  add.chromosome.ends = TRUE,
  use.recalculate.manual = FALSE,
  store.comp.times = TRUE,
  skip.rest = FALSE,
  enter.bv = TRUE,
  internal = FALSE,
  internal.geno = TRUE,
  internal.dataset = NULL,
  nbits = 30,
  bit.storing = FALSE,
  new.phenotype.correlation = NULL,
  length.before = 5,
  length.behind = 5,
  position.scaling = FALSE,
  shuffle.cor = NULL,
  shuffle.traits = NULL,
  bv.total = 0
)

Arguments

population	Population list
nsnp	Number of markers to generate (Split equally across chromosomes (chr.nr) unless vector is used)
nindi	Number of individuals to generate (you can also provide number males / females in a vector)
nqtl	Number of QTLs to generate (this will be a subset of the generated SNPs; default: NULL; all SNPs are potential QTLs)
name.cohort	Name of the newly added cohort
generation	Generation to which newly individuals are added (default: 1)
founder.pool	Founder pool an individual is assign to (default: 1)
one.sex.mode	Activating this will ignore all sex specific parameters and handle each individual as part of the first sex (default: FALSE)
database.sex.mode	Set TRUE to automatically remove females in selection.m and remove males in selection.f
sex.s	Specify which newly added individuals are male (1) or female (2)
sex.quota	Share of newly added female individuals (deterministic if sex.s="fixed", alt: sex.s="random")
class	Migration level of the newly added individuals (default: 0)
verbose	Set to FALSE to not display any prints
map	map-file that contains up to 5 colums (chromosome, SNP-id, M-position, Bp-position, allele freq - Everything not provides it set to NA). A map can be imported via MoBPSmaps::ensembl.map()
chr.nr	Number of chromosomes (SNPs are equally split) or vector containing the associated chromosome for each marker
chromosome.length	Length of the newly added chromosome in Morgan; can be a vector when generating multiple chromosomes (default: 5)
bp	Vector containing the physical position (bp) for each marker (default: 1,2,3...)
snps.equidistant	Use equidistant markers (computationally faster! ; default: TRUE)
template.chip	Import genetic map and chip from a species ("cattle", "chicken", "pig")
snp.position	Location of each marker on the genetic map
change.order	Markers are automatically sorted according to their snp.position unless this is set to FALSE (default: TRUE)
add.chromosome	If TRUE add an additional chromosome to the population
bpcm.conversion	Convert physical position (bp) into a cM position (default: 0 - not done)
snp.name	Vector containing the name of each marker (default ChrXSNPY - XY chosen accordingly)
hom0	Vector containing the first allelic variant in each marker (default: 0)
hom1	Vector containing the second allelic variant in each marker (default: 1)
dataset	SNP dataset, use "random", "allhetero" "all0" when generating a dataset via nsnp,nindi
freq	frequency of allele 1 when randomly generating a dataset (default: "beta" with parameters beta.shape1, beta.shape2; Use "same" when generating additional individuals and using the same allele frequencies)
beta.shape1	First parameter of the beta distribution for simulating allele frequencies
beta.shape2	Second parameter of the beta distribution for simulating allele frequencies
share.genotyped	Share of individuals genotyped in the founders
genotyped.s	Specify with newly added individuals are genotyped (1) or not (0)
vcf	Path to a vcf-file used as input genotypes (correct haplotype phase is assumed!)
vcf.maxsnp	Maximum number of SNPs to include in the genotype file (default: Inf)
vcf.maxindi	Maximum number of individuals to include in the genotype file (default: Inf)
vcf.chromosomes	Vector of chromosomes to import from vcf. Use on bgziped and tabixed vcf only. (default: NULL - all chromosomes)
vcf.VA	Use the VariantAnnotation package to load in a vcf file when available (default: TRUE)
trait.name	Name of the traits generated
mean.target	Target mean for each trait
var.target	Target variance for each trait
qtl.position.shared	Set to TRUE to put QTL effects on the same markers for different traits
trait.cor	Target correlation between QTL-based traits (underlying true genomic values)
trait.cor.include	Vector of traits to be included in the modelling of correlated traits (default: all - needs to match with trait.cor)
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 dominant QTL with equal effect size
n.overdominant	Number of overdominant QTL with effect size drawn from absolute value of a gaussian distribution
n.equal.overdominant	Number of overdominant QTL with equal effect size
n.qualitative	Number of qualitative epistatic QTL
n.quantitative	Number of quantitative epistatic QTL
effect.distribution	Set to "gamma" for gamma distribution effects with gamma.shape1, gamma.shape2 instead of gaussian (default: "gauss")
gamma.shape1	Default: 1
gamma.shape2	Default: 1
real.bv.add	Single Marker effects (list for each trait with columns for: SNP Nr, Chr Nr, Effect 00, Effect 01, Effect 11, Position (optional), Founder pool genotype (optional), Founder pool origin (optional))
real.bv.mult	Two Marker effects
real.bv.dice	Multi-marker effects
new.residual.correlation	Correlation of the simulated enviromental variance
new.breeding.correlation	Correlation of the simulated genetic variance (child share! heritage is not influenced!
litter.effect.covariance	Covariance matrix of the litter effect (default: no effects)
pen.effect.covariance	Covariance matrix of the pen effect (default: no effects)
is.maternal	Vector coding if a trait is caused by a maternal effect (Default: FALSE)
is.paternal	Vector coding if a trait is caused by a paternal effect (Default: FALSE)
fixed.effects	Matrix containing fixed effects (p x k -matrix with p being the number of traits and k being number of fixed effects; default: not fixed effects (NULL))
trait.pool	Vector providing information for which pools QTLs of which trait are activ (default: 0 - all pools)
gxe.correlation	Correlation matrix between locations / environments (default: only one location, sampled from gxe.max / gxe.min)
n.locations	Number of locations / environments to consider for the GxE model
gxe.max	Maximum correlation between locations / environments when generating correlation matrix via sampling (default: 0.85)
gxe.min	Minimum correlation between locations / environments when generating correlation matrix via sampling (default: 0.70)
location.name	Same of the different locations / environments used
gxe.combine	Set to FALSE to not view the same trait from different locations / environments as the sample trait in the prediction model (default: TRUE)
n.traits	Number of traits (If more than traits via real.bv.X use traits with no directly underlying QTL)
base.bv	Intercept of underlying true genomic values (excluding all QTL effects, default: 100)
dominant.only.positive	Set to TRUE to always assign the heterozygous variant with the higher of the two homozygous effects (e.g. hybrid breeding); default: FALSE
exclude.snps	Vector contain markers on which no QTL effects are placed
var.additive.l	Variance of additive QTL
var.dominant.l	Variance of dominante QTL
var.overdominant.l	Variance of overdominante 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
effect.size.equal.over	Effect size of the QTLs in n.equal.overdominant
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
set.zero	Set to TRUE to have no effect on the 0 genotype (or 00 for QTLs with 2 underlying SNPs)
bv.standard	Set TRUE to standardize trait mean and variance via bv.standardization() - automatically set to TRUE when mean/var.target are used
replace.real.bv	If TRUE delete the simulated traits added before
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!)
remove.invalid.qtl	Set to FALSE to deactive the automatic removal of QTLs on markers that do not exist
randomSeed	Set random seed of the process
add.architecture	Add genetic architecture (marker positions)
time.point	Time point at which the new individuals are generated
creating.type	Technique to generate new individuals (usage in web-based application)
size.scaling	Set to value to scale all input for breeding.size / selection.size (This will not work for all breeding programs / less general than json.simulation)
progress.bar	Set to FALSE to not use progress bars in any application of breeding.diploid() downstream (Keep log-files lean!)
miraculix	If TRUE use miraculix package for data storage, computations and dataset generation
miraculix.dataset	Set FALSE to deactivate miraculix package for dataset generation
add.chromosome.ends	Add chromosome ends as recombination points
use.recalculate.manual	Set to TRUE to use recalculate.manual to calculate genomic values (all individuals and traits jointly, default: FALSE)
store.comp.times	Set to FALSE to not store computing times needed to execute creating.diploid in $info$comp.times.creating
skip.rest	Internal variable needed when adding multiple chromosomes jointly
enter.bv	Internal parameter
internal	Do not touch!
internal.geno	Do not touch!
internal.dataset	Do not touch!
nbits	Bits available in MoBPS-bit-storing
bit.storing	Set to TRUE if the MoBPS (not-miraculix! bit-storing is used)
new.phenotype.correlation	(OLD! - use new.residual.correlation) Correlation of the simulated enviromental variance
length.before	Length before the first SNP of the dataset (default: 5)
length.behind	Length after the last SNP of the dataset (default: 5)
position.scaling	Manual scaling of snp.position
shuffle.cor	OLD! Use trait.cor - Target Correlation between traits
shuffle.traits	OLD! Use trait.cor.include - Vector of traits to be included for modelling of correlated traits (default: all - needs to match with shuffle.cor)
bv.total	OLD! Use n.traits instead. Number of traits (If more than traits via real.bv.X use traits with no directly underlying QTL)

Value

Population-list

Examples

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

MoBPS documentation built on Nov. 5, 2025, 6:26 p.m.