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

knitr::opts_chunk$set(echo = TRUE)

Problem 1: Sire Model

s_ex10_p01_data_path <- "https://charlotte-ngs.github.io/asmss2022/data/asm_ped_sim_data.csv"
if (!params$isonline)
  s_ex10_p01_data_path <- file.path(here::here(), "docs", "data", "asm_ped_sim_data.csv")

sigma_u2 <- 9
sigma_s2 <- sigma_u2 / 4
sigma_e2 <- 36

Use the following dataset to predict breeding values using a sire model. The dataset is available from

cat(s_ex10_p01_data_path, "\n")

Hints

• The variance component $\sigma_s^2$ of the sire effect can be assumed to be $r sigma_s2$.
• The variance component $\sigma_e^2$ of the random resiudals is $r sigma_e2$.
• Sex is modelled as a fixed effect.
• The sire pedigree relationship can be computed using the pedigreemm package.

Your Solution

• Read the data

• Compute the inverse sire relationship matrix

• Setup the mixed model equations

• Solve mixed model equations

Problem 2: Animal Model

s_ex10_p02_data_path <- "https://charlotte-ngs.github.io/asmss2022/data/asm_ped_sim_data.csv"
if (!params$isonline)
  s_ex10_p02_data_path <- file.path(here::here(), "docs", "data", "asm_ped_sim_data.csv")

sigma_u2 <- 9
sigma_s2 <- sigma_u2 / 4
sigma_e2 <- 36

Use the same dataset as in Problem 1 to predict breeding values, but use an animal model instead of a sire model. The dataset is available from

cat(s_ex10_p02_data_path, "\n")

Hints

• The variance component $\sigma_u^2$ of the breeding value can be assumed to be $r sigma_u2$.
• The variance component $\sigma_e^2$ of the random resiudals is $r sigma_e2$.
• Sex is modelled as a fixed effect.
• The numerator relationship matrix can be computed using the pedigreemm package.

Your Solution

• Read the data

• Compute the inverse sire relationship matrix

• Setup the mixed model equations

• Solve mixed model equations

Problem 3: Model Comparison

Compare the order of the predicted breeding values for the sires from the sire model and from the animal model.

Your Solution

• Compare both ordered vectors of predicted breeding values

cat('\n---\n\n _Latest Changes: ', format(Sys.time(), '%Y-%m-%d %H:%M:%S'), ' (', Sys.info()['user'], ')_\n', sep = '')

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