ggTutorial {nadiv}

Simulated dataset used to analyze data with genetic group animal models

Description

The dataset was simulated using the simGG function so that the pedigree contains a base population comprised of founders and non-founder immigrants. These data are then used in the main manuscript and tutorials accompanying Wolak & Reid (2017).

Usage

ggTutorial

Format

A data.frame with 6000 observations on the following 10 variables:

id

an integer vector specifying the 6000 unique individual identities

dam

an integer vector specifying the unique dam for each individual

sire

an integer vector specifying the unique sire for each individual

parAvgU

a numeric vector of the average autosomal total additive genetic effects (u) of each individual's parents

mendel

a numeric vector of the Mendelian sampling deviations from parAvgU autosomal total additive genetic effects that is unique to each individual

u

a numeric vector of the total autosomal additive genetic effects underlying p

r

a numeric vector of the residual (environmental) effects underlying p

p

a numeric vector of phenotypic values

is

an integer vector with 0 for individuals born in the focal population and 1 for individuals born outside of the focal population, but immigrated

gen

an integer vector specifying the generation in which each individual was born

Details

The dataset was simulated as described in the ‘examples’ section using the simGG function. Full details of the function and dataset can be found in Wolak & Reid (2017).

The data.frame contains 6000 individuals across 15 generations. In each generation, the carrying capacity is limited to 400 individuals, the number of mating pairs limited to 200 pairs, and 40 immigrants per generation arrive starting in the second generation.

The breeding values of the founders are drawn from a normal distribution with an expected mean of 0 and a variance of 1. The breeding values of all immigrants are drawn from a normal distribution with an expected mean of 3 and variance of 1. Consequently, the expected difference between mean breeding values in the founders and immigrants is 3. All individuals are assigned a residual (environmental) deviation that is drawn from a normal distribution with an expected mean of 0 and variance of 1.

Source

Wolak, M.E. & J.M. 2017. Accounting for genetic differences among unknown parents in microevolutionary studies: how to include genetic groups in quantitative genetic animal models. Journal of Animal Ecology 86:7-20. doi:10.1111/1365-2656.12597

Examples

 
  set.seed(102)     #<-- seed value used originally
  library(nadiv)
  # create data using `simGG()`
  ggTutorial <- simGG(K = 400, pairs = 200, noff = 4, g = 15,
    nimm = 40, nimmG = seq(2, 14, 1),		    # nimmG default value
    VAf = 1, VAi = 1, VRf = 1, VRi = 1,		    # all default values
    mup = 20, muf = 0, mui = 3, murf = 0, muri = 0, # mup and mui non-default values
    d_bvf = 0, d_bvi = 0, d_rf = 0, d_ri = 0)	    # all default values