rmvtnorm.pedigree function

Simulate residual multivariate Gaussian data from a polygenic model

Simulate residual multivariate Gaussian data from a polygenic model

Simulates residual multivariate Gaussian response data from a pedigree where the additive genetic, dominance genetic, and shared environmental effects are taken into account.

rmvtnorm.pedigree(n = 1, pedigree, h2 = 0, c2 = 0, d2 = 0)

Arguments

  • n: numeric. The number of simulations to generate
  • pedigree: a pedigree object
  • h2: numeric. The heritability
  • c2: numeric. The environmentability
  • d2: numeric. The dominance deviance effect

Returns

Returns a matrix with the simulated values with n columns (one for each simulation) and each row matches the corresponding individual from the pedigree

Details

The three parameters should have a sum: h2+c2+d2 that is less than 1. The total variance is set to 1, and the mean is zero.

Examples

library(kinship2) library(mvtnorm) mydata <- data.frame(id=1:5, dadid=c(NA, NA, 1, 1, 1), momid=c(NA, NA, 2, 2, 2), sex=c("male", "female", "male", "male", "male"), famid=c(1,1,1,1,1)) relation <- data.frame(id1=c(3), id2=c(4), famid=c(1), code=c(1)) ped <- pedigree(id=mydata$id, dadid=mydata$dadid, momid=mydata$momid, sex=mydata$sex, relation=relation) rmvtnorm.pedigree(2, ped, h2=.25)

See Also

pedigree, kinship,

Author(s)

Claus Ekstrom claus@rprimer.dk

  • Maintainer: Claus Thorn Ekstrøm
  • License: GPL-2
  • Last published: 2023-08-20