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
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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.