AquaBPsim (version 0.0.1)

select: Selection

Description

Function to select selection candidates based on their Index, EBV or phenotype. ped$selcand should be 1 for the selection candidates.

Usage

select(
  gen,
  batch = 0,
  select_on = "Index",
  trait,
  Ntraits = BPdata$Ntraits,
  Nm = BPdata$Nm,
  Nf = BPdata$Nf,
  max_FSfam = "all",
  mature_m = 1,
  mature_f = 1,
  selected = 1
)

Arguments

gen

The generation of the selection candidates. A vector with multiple generations can be provided.

batch

The batch of the selection candidates. Default is 0. It is possible to provide a vector with multiple batches.

select_on

Options: "Index", "EBV" or "Phenotype". For "EBV" and "Phenotype", also the trait need to be specified in 'trait'. Default is Index.

trait

Which trait or EBV the selection is base on when option "EBV" or "Phenotype" is choosen in 'select_on'.

Ntraits

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

Nm

Number of males to select.

Nf

Number of females to select.

max_FSfam

Maximum number of sibs that can be selected per full sib familie. Default is 'all'.

mature_m

Proportion of male selection candidates that is assumed to be mature and available at the moment of selection. Default is 1

mature_f

Proportion of female selection candidates that is assumed to be mature and available at the moment of selection. Default is 1

selected

The value assigned to ped$selected for the selected animals, default is 1.

Value

This function will change the data frame called 'ped'. Fish that are selected will be assigned a value to their column 'selected'.

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))
}

ped <- preselphen(gen = 1,
                  Nenv = 2,
                  Npresel = c(25,15),
                  trait = 1,
                  Ntraits = 2)
                  
ped <- avail_selection(gen = 1,
                       presel = 1,
                       surv = 0.9)
                       
ped <- breeding_values(gen = 1,
                       TraitsIndex = 2,
                       EBV = "GEBV",
                       GenomLength = 11.3,
                       Ne = 100,
                       SizeTraining = nrow(ped[ped$preselected ==2,]),
                       Ntraits = 2,
                       a_var = c(200,8000),
                       h2 = c(0.33,0.38))
                       
ped <- select(gen=1,
                 Nm = 60,
                 Nf = 60,
                 mature_m = 0.5,
                 mature_f = 0.4,
                 Ntraits = 2)
# }