In charlotte-ngs/asmss2022: Applied Statistical Methods in Animal Science - Spring Semester 2022

Disclaimer

Fit a sire model with pedigreemm

Data

tbl_sire_model <- tibble::tibble(Animal = c(4:8),
                                 Sire   = c(1,3,1,4,3),
                                 Sex    = c("M","F","F","M","M"),
                                 WWG    = c(4.5, 2.9, 3.9, 3.5, 5.0))
tbl_sire_model

Write the data to a file

s_sire_data_path <- file.path(here::here(), "docs", "data", "wwg_sire_data.csv")
if (!file.exists(s_sire_data_path))
  readr::write_csv(tbl_sire_model, file = s_sire_data_path)

Model

According to Vazquez2010, a sire model can be fit by first getting the pedigree

ped_sire <- pedigreemm::pedigree(sire = c(rep(NA,2), 1), dam = rep(NA,3), label = as.character(c(1,3,4)))
pedigreemm::getA(ped = ped_sire)

The inverse of $A$ is

pedigreemm::getAInv(ped = ped_sire)

The mixed model fit is done via

library(pedigreemm)
lmem_sire <- pedigreemm(
  formula = WWG ~ Sex + (1 | Sire), 
  data = tbl_sire_model,
  pedigree = list(Sire = ped_sire)
)

The results

summary(lmem_sire)

The breeding values

ranef(lmem_sire)

charlotte-ngs/asmss2022 documentation built on June 7, 2022, 1:33 p.m.