Datasets

This appendix describes all datasets used throughout the book. All datasets are available in the data/ directory and are free to use for teaching and learning purposes.

Datasets are realistic simulations based on published genetic parameters from the scientific literature. They are designed to illustrate breeding concepts while maintaining statistical properties consistent with real livestock data.

General Dataset Information

File Format

All datasets are provided as comma-separated values (.csv) files with:

Header row with variable names
One row per observation
Missing values coded as NA

Loading Data in R

library(tidyverse)

# Example: Load swine growth data
swine_data <- read_csv("data/swine_growth_heritability.csv")

# View structure
glimpse(swine_data)

Datasets by Chapter

Chapter 3: Basic Genetic Model

`swine_growth_basic.csv`

Description: Simulated growth data for 500 pigs to demonstrate the basic genetic model.

Variables:

pig_id: Unique pig identifier
breeding_value: True breeding value (kg)
environmental_effect: Environmental deviation (kg)
phenotype: Observed weaning weight (kg)

Parameters: h² = 0.30, σ²_P = 30 kg²

Chapter 5: Heritability and Repeatability

`swine_litter_size.csv`

Description: Litter size records for 300 sows across 3 parities.

Variables:

sow_id: Sow identifier
parity: 1, 2, or 3
total_born: Total pigs born
born_alive: Pigs born alive

Parameters: h² = 0.12, r = 0.18

`dairy_milk_repeated.csv`

Description: Milk yield across 3 lactations for 200 cows.

Variables:

cow_id: Cow identifier
lactation: 1, 2, or 3
milk_305: 305-day milk yield (kg)

Parameters: h² = 0.30, r = 0.50

Chapter 7: Estimating Breeding Values

`beef_weaning_weights.csv`

Description: Weaning weights for 500 beef calves with pedigree.

Variables:

calf_id, sire_id, dam_id: Identifiers
contemporary_group: Management group
weaning_weight: Weaning weight (kg)

Parameters: h² = 0.25, 10 contemporary groups

Chapter 8: Genetic Correlations

`dairy_yield_fertility.csv`

Description: Milk yield and fertility for 600 cows.

Variables:

cow_id: Cow identifier
milk_yield: 305-day milk (kg)
days_open: Days from calving to conception
BV_milk, BV_fertility: True breeding values

Parameters: h²_milk = 0.30, h²_fertility = 0.05, r_A = -0.35

Chapter 11: Crossbreeding

`swine_crossbreeding.csv`

Description: Litter size for purebred and crossbred sows.

Variables:

sow_id: Sow identifier
breed_type: “Large White”, “Landrace”, “LW x LR”
litter_size: Total born alive

Chapter 12-13: Genomics

`genotypes_example.csv`

Description: SNP genotypes for 100 animals (1000 SNPs), coded 0, 1, 2.

Data Citation

When using these datasets, please cite:

Putz, A. (2025). Animal Breeding and Genetics: A Practical Introduction for Undergraduate Students.

# Datasets {#sec-datasets .unnumbered} This appendix describes all datasets used throughout the book. All datasets are available in the `data/` directory and are free to use for teaching and learning purposes. Datasets are realistic simulations based on published genetic parameters from the scientific literature. They are designed to illustrate breeding concepts while maintaining statistical properties consistent with real livestock data. ## General Dataset Information ### File Format All datasets are provided as comma-separated values (`.csv`) files with: - Header row with variable names - One row per observation - Missing values coded as `NA` ### Loading Data in R ```r library(tidyverse) # Example: Load swine growth data swine_data <- read_csv("data/swine_growth_heritability.csv") # View structure glimpse(swine_data) ``` --- ## Datasets by Chapter ### Chapter 3: Basic Genetic Model #### `swine_growth_basic.csv` **Description**: Simulated growth data for 500 pigs to demonstrate the basic genetic model. **Variables**: - `pig_id`: Unique pig identifier - `breeding_value`: True breeding value (kg) - `environmental_effect`: Environmental deviation (kg) - `phenotype`: Observed weaning weight (kg) **Parameters**: h² = 0.30, σ²_P = 30 kg² --- ### Chapter 5: Heritability and Repeatability #### `swine_litter_size.csv` **Description**: Litter size records for 300 sows across 3 parities. **Variables**: - `sow_id`: Sow identifier - `parity`: 1, 2, or 3 - `total_born`: Total pigs born - `born_alive`: Pigs born alive **Parameters**: h² = 0.12, r = 0.18 --- #### `dairy_milk_repeated.csv` **Description**: Milk yield across 3 lactations for 200 cows. **Variables**: - `cow_id`: Cow identifier - `lactation`: 1, 2, or 3 - `milk_305`: 305-day milk yield (kg) **Parameters**: h² = 0.30, r = 0.50 --- ### Chapter 7: Estimating Breeding Values #### `beef_weaning_weights.csv` **Description**: Weaning weights for 500 beef calves with pedigree. **Variables**: - `calf_id`, `sire_id`, `dam_id`: Identifiers - `contemporary_group`: Management group - `weaning_weight`: Weaning weight (kg) **Parameters**: h² = 0.25, 10 contemporary groups --- ### Chapter 8: Genetic Correlations #### `dairy_yield_fertility.csv` **Description**: Milk yield and fertility for 600 cows. **Variables**: - `cow_id`: Cow identifier - `milk_yield`: 305-day milk (kg) - `days_open`: Days from calving to conception - `BV_milk`, `BV_fertility`: True breeding values **Parameters**: h²_milk = 0.30, h²_fertility = 0.05, r_A = -0.35 --- ### Chapter 11: Crossbreeding #### `swine_crossbreeding.csv` **Description**: Litter size for purebred and crossbred sows. **Variables**: - `sow_id`: Sow identifier - `breed_type`: "Large White", "Landrace", "LW x LR" - `litter_size`: Total born alive --- ### Chapter 12-13: Genomics #### `genotypes_example.csv` **Description**: SNP genotypes for 100 animals (1000 SNPs), coded 0, 1, 2. --- ## Data Citation When using these datasets, please cite: > Putz, A. (2025). *Animal Breeding and Genetics: A Practical Introduction for Undergraduate Students.*