An interactive R Shiny application for analyzing genomic prediction results in sheep, focusing on methane emissions and feed efficiency traits using microbiome-enhanced genomic prediction models.
Objective 1: Evaluate PCA effectiveness in reducing rumen microbiome data dimensionality while retaining essential biological information.
Objective 2: Assess whether incorporating PCA-reduced microbiome data as intermediate traits in Neural Network GBLUP improves genomic prediction accuracy for methane emissions and feed efficiency traits.
Access the interactive application at: https://setalemu.shinyapps.io/genomics_app_deploy/
- Interactive visualizations of PCA analysis
- Microbiability estimates across PC thresholds
- Genomic prediction results (Train-Test and Five-Fold validation)
- Model comparisons (G, GM, NN-GBLUP)
- Downloadable plots and supplementary materials
- Comprehensive data tables
# Install required packages
packages <- c("shiny", "shinydashboard", "dplyr", "tidyr",
"ggplot2", "DT", "RColorBrewer", "gridExtra",
"cowplot", "grid", "shinyjs")
install.packages(packages)
# Run the application
shiny::runApp()