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

Use the package pedSimulate to generate a pedigree with data

library(pedSimulate)
ped <- simulatePed(
  F0size = 4,
  Va0 = 16,
  Ve = 64,
  littersize = 2,
  ngen = 2,
  overlap.s = 1,
  m.rate = 0.5,
  seed = 1973
)

Show the data

ped

Replace dam 4 with NA and remove the record of that animal

ped$DAM[ped$DAM == 4] <- NA
ped <- ped[-4,]
ped

Adapt IDs

ped$ID <- 1:nrow(ped)
ped$SIRE[which(ped$SIRE > 4)] <- ped$SIRE[which(ped$SIRE > 4)] - 1
ped$DAM[which(ped$DAM > 4)] <- ped$DAM[which(ped$DAM > 4)] - 1
ped

Adding a fixed sex effect

We want to add a fixed effect for sex

vec_sex_eff <- c(-5.1, 3.7)
mat_X_sex <- model.matrix(lm(ped$P ~ 0 + ped$SEX))
attr(mat_X_sex, "assign") <- NULL
attr(mat_X_sex, "contrasts") <- NULL
mat_X_sex

mat_sex_eff <- mat_X_sex %*% vec_sex_eff
mat_sex_eff

ped$P <- as.vector(ped$P + mat_sex_eff[,1])
ped$P <- round(ped$P, digits = 1)
ped

Write Data to File

Prepare output

library(dplyr)
tbl_ped <- tibble::as_tibble(ped)
# select relevant columns
tbl_ped_data_out <- ped %>%
  select(ID, SIRE, DAM, SEX, P)
# set unknown paretns to NA
tbl_ped_data_out$SIRE[tbl_ped_data_out$SIRE == 0] <- NA
tbl_ped_data_out$DAM[tbl_ped_data_out$DAM == 0] <- NA
tbl_ped_data_out <- tbl_ped_data_out %>% filter(ID > 3)
tbl_ped_data_out

Write data to file

s_data_out_path <- file.path(here::here(), "docs", "data", "asm_exam_p04.csv")
if (!file.exists(s_data_out_path))
  readr::write_csv(tbl_ped_data_out, s_data_out_path)

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