Generation of the starting population
creating.diploid(
dataset = NULL,
vcf = NULL,
chr.nr = NULL,
bp = NULL,
snp.name = NULL,
hom0 = NULL,
hom1 = NULL,
bpcm.conversion = 0,
nsnp = 0,
nindi = 0,
freq = "beta",
population = NULL,
sex.s = "fixed",
add.chromosome = FALSE,
generation = 1,
class = 0L,
sex.quota = 0.5,
chromosome.length = NULL,
length.before = 5,
length.behind = 5,
real.bv.add = NULL,
real.bv.mult = NULL,
real.bv.dice = NULL,
snps.equidistant = NULL,
change.order = FALSE,
bv.total = 0,
polygenic.variance = 100,
bve.mult.factor = NULL,
bve.poly.factor = NULL,
base.bv = NULL,
add.chromosome.ends = TRUE,
new.phenotype.correlation = NULL,
new.residual.correlation = NULL,
new.breeding.correlation = NULL,
add.architecture = NULL,
snp.position = NULL,
position.scaling = FALSE,
bit.storing = FALSE,
nbits = 30,
randomSeed = NULL,
miraculix = TRUE,
miraculix.dataset = TRUE,
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,
replace.real.bv = FALSE,
shuffle.traits = NULL,
shuffle.cor = NULL,
skip.rest = FALSE,
enter.bv = TRUE,
name.cohort = NULL,
template.chip = NULL,
beta.shape1 = 1,
beta.shape2 = 1,
time.point = 0,
creating.type = 0,
trait.name = NULL,
share.genotyped = 1,
genotyped.s = NULL,
map = NULL,
remove.invalid.qtl = TRUE,
verbose = TRUE,
bv.standard = FALSE,
mean.target = NULL,
var.target = NULL,
is.maternal = NULL,
is.paternal = NULL,
vcf.maxsnp = Inf,
internal = FALSE
)SNP dataset, use "random", "allhetero" "all0" when generating a dataset via nsnp,nindi
Path to a vcf-file used as input genotypes (correct haplotype phase is assumed!)
Vector containing the assosiated chromosome for each marker (default: all on the same)
Vector containing the physical position (bp) for each marker (default: 1,2,3...)
Vector containing the name of each marker (default ChrXSNPY - XY chosen accordingly)
Vector containing the first allelic variant in each marker (default: 0)
Vector containing the second allelic variant in each marker (default: 1)
Convert physical position (bp) into a cM position (default: 0 - not done)
number of markers to generate in a random dataset
number of inidividuals to generate in a random dataset
frequency of allele 1 when randomly generating a dataset
Population list
Specify which newly added individuals are male (1) or female (2)
If TRUE add an additional chromosome to the dataset
Generation of the newly added individuals (default: 1)
Migration level of the newly added individuals
Share of newly added female individuals (deterministic if sex.s="fixed", alt: sex.s="random")
Length of the newly added chromosome (default: 5)
Length before the first SNP of the dataset (default: 5)
Length after the last SNP of the dataset (default: 5)
Single Marker effects
Two Marker effects
Multi-marker effects
Use equidistant markers (computationally faster! ; default: TRUE)
If TRUE sort markers according to given marker positions
Number of traits (If more than traits via real.bv.X use traits with no directly underlying QTL)
Genetic variance of traits with no underlying QTL
Multiplicate trait value times this
Potency trait value over this
Average genetic value of a trait
Add chromosome ends as recombination points
(OLD! - use new.residual.correlation) Correlation of the simulated enviromental variance
Correlation of the simulated enviromental variance
Correlation of the simulated genetic variance (child share! heritage is not influenced!
Add genetic architecture (marker positions)
Location of each marker on the genetic map
Manual scaling of snp.position
Set to TRUE if the MoBPS (not-miraculix! bit-storing is used)
Bits available in MoBPS-bit-storing
Set random seed of the process
If TRUE use miraculix package for data storage, computations and dataset generation
Set FALSE to deactive miraculix package for dataset generation
Number of additive QTL with effect size drawn from a gaussian distribution
Number of additive QTL with equal effect size (effect.size)
Number of dominant QTL with effect size drawn from a gaussian distribution
Number of n.equal.dominant QTL with equal effect size
Number of qualitative epistatic QTL
Number of quantitative epistatic QTL
Set to TRUE to always asign the heterozygous variant with the higher of the two homozygous effects (e.g. hybrid breeding); default: FALSE
Variance of additive QTL
Variance of dominante QTL
Variance of qualitative epistatic QTL
Variance of quantitative epistatic QTL
Effect size of the QTLs in n.equal.additive
Effect size of the QTLs in n.equal.dominant
Marker were no QTL are simulated on
If TRUE delete the simulated traits added before
Combine different traits into a joined trait
Target Correlation between shuffeled traits
Internal variable needed when adding multipe chromosomes jointly
Internal parameter
Name of the newly added cohort
Import genetic map and chip from a species ("cattle", "chicken", "pig")
First parameter of the beta distribution for simulating allele frequencies
Second parameter of the beta distribution for simulating allele frequencies
Time point at which the new individuals are generated
Technique to generate new individuals (usage in web-based application)
Name of the trait generated
Share of individuals genotyped in the founders
Specify with newly added individuals are genotyped (1) or not (0)
map-file that contains up to 5 colums (Chromsome, SNP-id, M-position, Bp-position, allele freq - Everything not provides it set to NA). A map can be imported via MoBPSmaps::ensembl.map()
Set to FALSE to deactive the automatic removal of QTLs on markers that do not exist
Set to FALSE to not display any prints
Set TRUE to standardize trait mean and variance via bv.standardization() - automatically set to TRUE when mean/var.target are used
Target mean
Target variance
Vector coding if a trait is caused by a maternal effect (Default: all FALSE)
Vector coding if a trait is caused by a paternal effect (Default: all FALSE)
Maximum number of SNPs to include in the genotype file (default: Inf)
Dont touch!
Population-list
# NOT RUN {
population <- creating.diploid(nsnp=1000, nindi=100)
# }
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