AquaBPsim (version 0.0.1)

offspringFSfam: Creating offspring for family design

Description

This function can be used to create the offspring of one full sib family in a family design, with genetic, common environmental and residual effects for each offspring. Offspring are added to the ped file.

Usage

offspringFSfam(
  gen,
  No,
  sire,
  dam,
  batch = 0,
  probmale = BPdata$prob_male,
  Ntraits = BPdata$Ntraits,
  TraitsIndex = c(1:Ntraits),
  Rgen = BPdata$Rgen,
  Rres = BPdata$Rres,
  Rcom = BPdata$Rcom,
  a_var = BPdata$a_var,
  c_var = BPdata$c_var,
  e_var = BPdata$e_var,
  inbreeding = TRUE
)

Arguments

gen

The generation of the offspring.

No

The number of offspring per fullsib family.

sire

The sire of the full sib family. Sire should also be in the ped file with information on the inbreeding level and true breeding values for each trait.

dam

The dam of the full sib family. Dam should also be in the ped file with information on the inbreeding level and the true breeding values for each trait.

batch

The batch of the offspring. Default is 0.

probmale

The probability that a offspring is male. The probability that the offspring is female is calculated as 1 - probmale. Probmale does not need to be specified if it is in the list called 'BPdata'. The default is 0.5.

Ntraits

Number of traits to be simulated. Does not need to be specified if Ntraits is in the list 'BPdata'.

TraitsIndex

Vector of traits that are in the selection index. By default, all traits are in the index.

Rgen

Matrix of all genetic correlations between all Ntraits. Only needs to be specified if there is no matrix of genetic correlations named Rgen in the list called 'BPdata'.

Rres

Matrix of all residual correlations between all Ntraits. Only needs to be specified if there is no matrix of residual correlations named Rres in the list called 'BPdata'.

Rcom

Matrix of all common environmental correlations between all Ntraits. Only needs to be specified if there is no matrix of common environmental correlations named Rcom in the list called 'BPdata'.

a_var

Vector of genetic variances of all traits. Only needs to be specified if there is no vector of genetic variances named a_var in the list called 'BPdata'.

c_var

Vector of common environmental variances of all traits. Only needs to be specified if there is no vector of common environmental variances named c_var in the list called 'BPdata'.

e_var

Vector of residual variances of all traits. Only needs to be specified if there is no vector of residual variances named e_var in the list called 'BPdata'.

inbreeding

If TRUE (default), then the inbreeding level is calculated for each offspring.

Value

This function returns the 'ped' data frame: the new offspring are added to this data frame.

Examples

# NOT RUN {
ped <- founderpopfam(Nm = 60,
                     Nf = 60,
                     Nm2 = 0,
                     Nf2 = 0,
                     Ntraits = 2,
                     TraitsIndex = 2,
                     Rgen = matrix(c(1.00   , 0.48,
                                    0.48   , 1.00),
                                 nrow = 2),
                     Rcom = matrix(c(1.00  , 0.5,
                                    0.5   , 1.00),
                                 nrow = 2),
                     Rres = matrix(c(1.00   , 0.32,
                                    0.32   , 1.00),
                                 nrow = 2),
                     mean = c(50,500),
                     a_var = c(200,8000),
                     c_var = c(150,1000),
                     e_var = c(250,12000))
                     
Mating <- randommating(gen = 0,
                       Nfam_FS = 120)

for(fam in 1: nrow(Mating)){
ped <- offspringFSfam(gen = 1,
                      No = 100,
                      probmale = 0.5,
                      sire = Mating$Sire[fam],
                      dam = Mating$Dam[fam],
                      Ntraits = 2,
                      TraitsIndex = 2,
                      Rgen = matrix(c(1.00   , 0.48,
                                    0.48   , 1.00),
                                 nrow = 2),
                      Rcom = matrix(c(1.00  , 0.5,
                                    0.5   , 1.00),
                                 nrow = 2),
                      Rres = matrix(c(1.00   , 0.32,
                                    0.32   , 1.00),
                                 nrow = 2),
                      a_var = c(200,8000),
                      c_var = c(150,1000),
                      e_var = c(250,12000))
}
# }