🧬 Pan-Cancer Analysis User Interface

The Pan-Cancer Analysis User Interface is an advanced interactive tool designed to facilitate the analysis of genomic variations, mutation patterns, and multi-omics data across various cancer types. This platform empowers researchers, bioinformaticians, and clinicians with powerful visualizations and data insights to uncover meaningful patterns in cancer-related data.

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🌟 Key Features

🔬 Multi-Omics Analysis

• Copy Number Variations (CNV): Visualize large-scale changes in genomic structure with customizable heatmaps.
• Transcriptome Data: Explore gene expression profiles and identify potential biomarkers.
• Single Nucleotide Variations (SNV): Pinpoint mutation hotspots across different cancer types.

📊 Interactive Visualizations

• Dynamic Heatmaps: Customize color schemes, annotations, and clustering options.
• Correlation Matrices: Analyze relationships between genomic features and expression levels.
• Pie Charts & Bar Graphs: Gain deeper insights into mutation distributions and gene expression profiles.

🏰 Global Overview

• Integration of geographic data for global comparisons in mutation prevalence.

⚙️ Advanced Customization

• Fully customizable visualization parameters to suit diverse analytical needs.
• Real-time data filtering for targeted analysis.

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💻 Technology Stack

• Frontend: Shiny framework for a responsive and user-friendly interface.
• Backend: R for data processing, machine learning, and visualization.
• Visualization Tools: ggplot2, Plotly for interactive and publication-quality graphics.
• Data Handling: data.table for efficient manipulation of large datasets.

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🚀 Getting Started

Prerequisites

1. Install R (version 4.0 or newer).
2. Install the required R packages:

   install.packages(c("shiny", "ggplot2", "data.table", "plotly", "DT", "reshape2"))

Clone the Repository

git clone https://github.com/ozeraysenur/SeniorProject.git
cd SeniorProject

Run the Application

shiny::runApp("app")

Access the App

Navigate to http://localhost:8100 in your web browser.

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📂 Repository Structure

SeniorProject/
├── app/                   # Shiny app components
│   ├── ui.R               # User interface
│   ├── server.R           # Backend server logic
│   └── helpers.R          # Helper functions
├── data/                  # Input datasets
├── assets/                # Images and custom CSS
├── scripts/               # Data preprocessing and analysis scripts
└── README.md              # Project documentation

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📊 Dataset Description

• Source: Public cancer genome datasets.
• Structure:
  • Mutation profiles per sample.
  • Gene expression levels across cancer types.
  • Clinical annotations for patient stratification.

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✨ Advanced Features

🔍 Data Insights

• Heatmap visualizations with hierarchical clustering.
• Gene and sample filtering for focused analysis.
• Mutation density distributions.

📦 Data Export

• Export filtered and analyzed data in CSV and JSON formats.

🧠 Machine Learning Integration

• Incorporation of clustering algorithms to identify sample subtypes.
• Regression analysis for gene expression predictions.

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📜 How to Contribute

We welcome contributions!

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a clear description of your changes.

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💜 Acknowledgements

This project was developed as part of a senior thesis project to advance cancer research through data visualization and analysis. A heartfelt thank you to all mentors, collaborators, and the open-source community for their support.

Made with 💜 by Ayşenur Özer