Welcome to the GeoPopMap Tutorial

Project Contributors

Developer & Tutorial Author

• Mohamad Yassine (mohamad.a.ysn@gmail.com)

Collaborators

• Sarah Ben Sadoun (sarah.ben-sadoun@inrae.fr)

• Yannick Olivier (yannick.olivier@inrae.fr)

• Stephane Nicolas (stephane.nicolas@inrae.fr)

• Franck Gauthier (franck.gauthier@inrae.fr)

• Agustin-Oscar Galaretto (agustin-oscar.galaretto@inrae.fr)

• Valentin Bourdin (valentin.bourdin1@etu.u-paris.fr)

This tutorial will guide you through the process of using GeoPopMap, a comprehensive R Shiny application for analyzing and visualizing multi-dimensional agricultural data.

The main interface of the GeoPopMap application.

Getting Started

This tutorial is divided into several sections, each covering a specific aspect of the application. We recommend following them in order to get a complete understanding of the workflow.

Tutorial Contents:

• Prerequisites
  • Required Software
  • System Dependencies
  • Required R Packages
  • Next Steps
• Usage
  • Installation Steps
  • Running the Application
  • Test Data
  • Next Steps
• Data Management and Merging
  • Interface Overview
  • Advanced Import Options (Common to All Data Types)
  • Details by Data Type
  • Actions After Import
  • Merging Data
  • Tips and Best Practices
  • Visual Summary of Options by Data Type
  • Next Steps
• Map Visualization
  • 1. Accessing the Map Interface
  • 2. Map Display and Navigation
  • 3. Coloring and Variable Selection
  • 4. Advanced Customization
  • 5. Interactive Point Selection
  • 6. Viewing and Exporting Selected Data
  • 7. Reset and Export Map
  • 8. Use Cases and Best Practices
  • Next Steps
• Principal Component Analysis (PCA)
  • Overview
  • 1. Analysis Type: PCA vs PCoA
  • 2. Variable Selection
  • 3. PCA Parameters
  • 4. Visualization Modes
  • 5. Grouping and Coloring
  • 6. Plot Customization
  • 7. Variance Explained
  • 8. Variable Contributions
  • 9. Data Export
  • 10. Interactive Plot
  • 11. Handling Missing Data
  • 11. Example Workflow
  • Best Practices
  • Next Steps
• Correlation Analysis
  • 1. Variable Selection
  • 2. Running the Analysis
  • 3. Results and Visualization
  • 4. Plot Customization
  • 5. Export
  • 6. Handling Missing Data
  • 7. Example Workflow
  • 8. Best Practices
  • Next Steps
• ANOVA Analysis
  • 1. When is ANOVA available?
  • 2. How to perform the analysis
  • 3. Interpreting the Results
  • 4. Exporting Results
  • 5. Best Practices
  • 6. Limitations
  • Next Steps
• Statistical Analysis
  • 1. The Statistical Analysis Interface
  • 2. Variable Selection and Data Scope
  • 3. Distribution and Summary for All Data
  • 4. Distribution and Summary for Selected Data
  • 5. Interpreting the Results
  • 6. Exporting Results
  • 7. Best Practices
  • Next Steps

Introduction to GeoPopMap

GeoPopMap is a comprehensive R Shiny application designed for the analysis and visualization of multi-dimensional agricultural data. The application provides an integrated platform for handling and analyzing climatic, genotypic, and phenotypic data with a focus on spatial relationships and statistical analysis.

Key Features

• Data Upload and Validation: Supports various data formats and validates data to ensure quality.

• Data Merging: Merge different datasets to create a comprehensive analysis-ready dataset.

• Interactive Map Visualization: Visualize geographic data and explore spatial patterns.

• PCA and Correlation Analysis: Perform statistical analyses to uncover relationships in your data.

• ANOVA and Statistical Summaries: Conduct analysis of variance and generate statistical summaries.

About This Tutorial

This tutorial is designed to be interactive. At each step, we will show you what to do and what to expect. We will use placeholders for screenshots that you can replace with your own as you follow along.

Let’s begin by setting up the required prerequisites.