Quantitative Genetics/R programming/ Linear models
We will focus on quantitative genetics, especially on:
Review of Quantitative genetics/ Quantitative trait loci
Sources of quantitative trait variation
Breeding Values and Heritabilities
Response from selection
Resemblance among relatives
Big Picture of Genomic selection/ Machine learning approach
Linear Models/ANOVA/GLM
Genomic Selection in R
Factors affecting Genomic Selection
Optimization of GS
Fixed-Random Effects
Best Linear Unbiased Estimator
Best Linear Unbiased Predictor
Statistical concepts for Genomic Selection analysis in R
Pedigree vs. Kinship matrix
Imputation
Statistical Models
Genotype X Environment interaction
Multi-trait analysis
Hybrid prediction
Statistical Analysis in Genomic Selection: Genomic Mating
One-step model
Two-Step models
Cross-Validations
Parental proportion and genomic mating