Application Guide

Welcome to the user guide for Arabidopsis Gene Network Explorer (AGNE). This document will help you understand how to use the application, the purpose of each feature, and how to interpret the results generated.

Overview

The AGNE application provides a platform for analyzing gene expression data, performing network visualization, and conducting functional enrichment analysis in Arabidopsis thaliana.

Key Features: - Upload and preprocess gene expression data. - Generate volcano plots for differential expression analysis. - Visualize gene interaction networks. - Perform GO and KEGG enrichment analyses. - Export results and plots for reporting.

Getting Started

1. Upload Your Data - The application accepts CSV files for the following:

  • Normalized Data: Contains gene expression levels.

  • Differentially Expressed Genes (DEGs): Contains log fold change (logFC) and adjusted p-values for genes.

  • Genes of Interest: An optional list of specific genes you want to focus on.

Data Format Requirements: - Normalized Data: Gene IDs as rows and sample names as columns. - DEGs: A CSV file with the following columns:

  • Gene_ID

  • logFC

  • p.adjust (adjusted p-value)

  • Genes of Interest: A list of `Gene_ID`s (one per line).

2. Set Analysis Parameters - Use the sidebar to define analysis thresholds:

  • logFC Threshold: Specify the minimum fold change for differential expression.

  • p-value Threshold: Set the significance level for adjusted p-values.

  • Regulation Type: Choose between Upregulated, Downregulated, or Both.

3. Run Analysis - Click the “Run Analysis” button to process the uploaded data and generate results.

Features and Outputs

### Volcano Plot The Volcano Plot visualizes the relationship between log fold change and significance (adjusted p-value) for all genes: - X-axis: log2(Fold Change) - Y-axis: -log10(Adjusted p-value) - Color Coding:

  • Red: Overexpressed genes.

  • Blue: Underexpressed genes.

  • Grey: Non-significant genes.

  • Hover over points to see gene-specific details.

How to Use: - Select genes of interest by dragging over the plot. - Selected genes will appear in the table below the plot.

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### Gene Interaction Network The Network Visualization explores relationships between genes based on co-expression or known interactions: - Nodes represent genes. - Edges represent interactions.

How to Customize: - Adjust network layout, node size, and edge thickness. - Highlight genes of interest by uploading a list of `Gene_ID`s.

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### GO Enrichment Analysis The Gene Ontology (GO) Analysis identifies overrepresented biological functions in your gene set: - Categories:

  • Biological Process (BP)

  • Molecular Function (MF)

  • Cellular Component (CC)

  • Output: - Barplot of top GO terms. - Table of enriched terms with p-values and associated genes.

How to Interpret: - Higher bar height indicates stronger enrichment. - Click GO terms to open detailed descriptions on external websites.

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### KEGG Enrichment Analysis The KEGG Analysis identifies pathways enriched in your gene set: - Output:

  • Barplot of top KEGG pathways.

  • Table with pathway details and associated genes.

How to Interpret: - Larger Rich Factor values indicate stronger pathway involvement. - Click KEGG IDs to explore pathways interactively.

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### Exporting Results You can export: - Plots: Download as PNG or PDF. - Tables: Save as CSV or Excel files.

Tips for Effective Use

  • Ensure your data files are correctly formatted before uploading.

  • Start with broader thresholds (e.g., lower logFC and higher p-value) to get an overview, then refine your filters.

  • Use the interactive plots to explore and validate your hypotheses.

Understanding Results

  • Differentially expressed genes help identify key players in the conditions being studied.

  • Gene Ontology and KEGG pathways provide biological context to your results.

  • Network visualization reveals relationships and central nodes within your data.

FAQs

1. What if my data file doesn’t upload? - Check that the file format is CSV and meets the required column structure.

2. Why does my Volcano Plot show no significant genes? - Ensure your thresholds (logFC and p-value) are not too strict.

3. Can I analyze non-Arabidopsis species? - The application is tailored to Arabidopsis thaliana. For other species, ensure appropriate databases are available.

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We hope this guide helps you make the most of the AGNE application. For further assistance, please contact the development team or refer to the full documentation.