October 29, 2019 Software Open Access

matthewwolak/nadiv: CRAN v2.16.2

Matthew

2.16.2.0 NEW

• geneDrop() conducts a gene dropping simulation down a user-supplied pedigree.

• simGG() now simulates phenotypes with heterogeneous additive genetic variances among the genetic groups (i.e., immigrant and resident groups)
  • The change to this simulation function now ensures phenotypes and underlying breeding values are consistent with the mixed model genetic group analysis approach described by Muff et al. 2019. Gen. Sel. Evol.
  • Breeding values have now been "split" to track resident-specific and immigrant-specific breeding values
  • Users should interact with the function the same way as always, as no changes to the function arguments have been made.
• makeGGAinv() added as a new function to construct genetic group-specific inverse relatedness matrices (Ainv).
  • implements the approach in Muff et al. 2019. Gen. Sel. Evol.
  • An example is given in the help documentation (in R, run ?makeGGAinv), but below is a basic example:

    ggPed <- Q1988[-c(3:7), c("id", "damGG", "sireGG")]
    AinvOut <- makeGGAinv(ggPed, ggroups = 2)$Ainv  #<-- list with 2 Ainv matrices
    

• added makeTinv() and makeDiiF() functions
  • These create items used in the Cholesky factorization of a relatedness matrix (or its inverse) and/or the individual coefficients of inbreeding f
  • In particular, these are used to construct genetic group specific inverse relatedness matrices, and are used "under the hood" in makeGGAinv().
  • makeDiiF() creates the D matrix of the Cholesky factorization of the relatedness matrix below (i.e., A and the coefficients of inbreeding (diagonals-1 of A)
  • makeTinv() creates Tinv of the Cholesky factorization of the inverse relatedness matrix below (i.e., Ainv)
    • A= T' D T
    • Ainv=Tinv' Dinv Tinv
  • Note, because D and Dinv are diagonal matrices, Dinv= the element-wise operation of 1 / d_ii
    • Consequently, obtaining Dinv from D is trivial
    • Simply do Dinv <- D followed by Dinv@x <- 1 / D@x
  • Users only need to supply a pedigree and the functions do the rest. For example:

    makeTinv(Mrode2)
    makeDiiF(Mrode2)