select: Selection

In AquaBPsim: Aquaculture Breeding Program Simulation

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

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)

AquaBPsim documentation built on March 18, 2022, 6:40 p.m.