CNVizard

CNVizard is a powerful, Streamlit-based application designed for the visualization and analysis of germline copy number variants (CNVs). This tool provides a streamlined interface for researchers and clinicians to analyze genetic data, create and manage references, and visualize CNV datasets.

Table of Contents

• Features
• Installation
  • Install via PyPI
  • Install via Docker
  • Install from Source
  • Optional OMIM Annotations
• Usage
  • Running the Application
  • Creating References
  • Visualizing Data
• License

Features

• Visualizes and analyzes germline copy number variants (CNVs)
• Integration with CNVkit-generated .cnr and .bintest files
• Supports trio analysis and scatter plots
• Generates customizable references
• OMIM-based CNV annotations
• Exportable filtered datasets and visualizations

Installation

Install via PyPI

CNVizard can be easily installed from PyPI:

1. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

2. Install CNVizard:

   pip install CNVizard

3. Run the application:

   python -m cnvizard.run <ENV>

Install via Docker

You can quickly run CNVizard using Docker without setting up a Python environment:

1. Pull the Docker image:

   docker pull ghcr.io/ihggm-aachen/cnvizard

2. Run the Docker container:

   docker run -p 8501:8501 cnvizard

3. Access the Streamlit app: Open your browser and navigate to http://localhost:8501 to start using CNVizard.

Install from Source

To install CNVizard from source, follow these steps:

1. Clone the repository:

   git clone https://github.com/IHGGM-Aachen/CNVizard
   cd CNVizard

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install the dependencies:

   pip install -e .

4. Ensure you have Tabix installed (required for processing CNVkit .vcf.gz files).

5. Run the application:

   streamlit run cnvizard/app.py <ENV>

Optional OMIM Annotations

CNVizard allows you to annotate CNVs with information from OMIM (Online Mendelian Inheritance in Man). OMIM is a copyrighted resource, so we cannot provide these files.

If you wish to use OMIM annotations:

• Obtain a license from OMIM.
• Reformat the morbidmap.txt file into a tab-delimited .txt file with the following column names:

  gene  OMIMG Disease  OMIMP Inheritance
  

Dependencies and Compatibility

Dependencies:

• Tabix: CNVizard requires Tabix for processing .vcf.gz files. Tabix can be installed directly over some pacakge management systems or by downloading directly from Samtools.

Pitfalls:

• Browser Compatibility: CNVizard works well on most browsers, but some users have reported issues when using Safari. We recommend using Firefox for the best experience.

Usage

Running the Application

1. Start the application: If using the Docker container, it will be accessible at http://localhost:8501. If installed from PyPi, run:

   python -m cnvizard.run <ENV>

   Or if installed from source, run:

   streamlit run cnvizard/app.py <ENV>

2. Set up the environment:

   • Optional: Provide an environment file (.env) during startup or upload one through the app interface. This file can contain paths to OMIM annotations, candidate lists, and references.
   • If no .env file is specified, the app will prompt you to upload or create one.

3. Upload data files:

   • Upload .cnr, .bintest, or .vcf.gz files generated by CNVkit.

Creating References

1. Reference Creation: CNVizard allows you to create reference files from .cnr data. You can specify the type of reference (normal or bintest) and provide paths for input and output data.

2. Merging References: If you have previously created individual reference files, you can merge them into a consolidated reference.

3. Convert Genomics England Panel: CNVizard provides a tool to convert Genomics England panel files into a compatible format.

Visualizing Data

1. CNV Analysis:

   • Upload .cnr and .bintest files for sample analysis.
   • Apply filters for chromosomes, depth, log2 ratio, or specific genes.

2. Trio Analysis:

   • You can perform trio analysis by uploading .cnr files from parents.

3. Scatter Plots:

   • CNVizard supports genome-wide and chromosome-wide scatter plots.
   • Combine .cnr, .cns, and .vcf.gz files to visualize data points across the genome.

4. Export Results:

   • Filtered dataframes and visualizations can be exported as Excel files for further analysis.

License

This project is licensed under the MIT License. See the LICENSE file for more information.