A Beginner’s Guide to Visualizing Genomic Feature Data

Visualizing genomic feature data is crucial for understanding complex biological processes, identifying patterns, and deriving insights from genomic data. This guide outlines step-by-step instructions for visualizing genomic data using modern tools and techniques, with a focus on user-friendly tools and scripts in Python, Unix, and Perl.

Why Visualize Genomic Data?

1. Importance:
   • Understanding gene structure and function.
   • Identifying variants and their genomic context.
   • Comparing different genomic datasets.
2. Uses and Applications:
   • Diagnostics and personalized medicine.
   • Functional genomics research.
   • Genomic data interpretation in agriculture and evolution.

Common Formats for Genomic Data

• GFF/GTF: Gene annotations.
• BED: Feature-based annotations.
• FASTA: Sequence data.
• SAM/BAM: Alignment data.
• VCF: Variant data.

Tools for Genomic Visualization

1. Integrated Genome Viewer (IGV)

• Description: A powerful desktop application for visualizing genomic data.
• Installation:
  bash

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  wget https://data.broadinstitute.org/igv/projects/downloads/IGV_2.16.0.zip
unzip IGV_2.16.0.zip
cd IGV_2.16.0
./igv.sh

• Features:
  • Supports multiple formats (BAM, VCF, BED).
  • Custom track addition.
  • Zoom in/out to visualize gene details.

2. UCSC Genome Browser

• Description: A web-based genome browser for visualizing genomic annotations.
• Custom Tracks:
  1. Format your data as BED or GFF.
  2. Upload it via the Custom Tracks interface.
  • Example BED snippet:
    arduino

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    track name="My Track" description="Custom Data" visibility=2
chr1 1000000 1000100


3. JBrowse

• Description: A modern, web-based genome browser.
• Installation:
  bash

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  git clone https://github.com/GMOD/jbrowse.git
cd jbrowse
./setup.sh

• Custom Tracks:
  • Add tracks via trackList.json configuration.
  • Example:
    json

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    {
"tracks": [
{
"label": "MyTrack",
"urlTemplate": "data/mytrack.bam",
"type": "JBrowse/View/Track/Alignments"
}
]
}


4. Circos

• Description: Visualizes genomic relationships in a circular format.
• Installation:
  bash

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  sudo apt install circos

• Usage:
  • Prepare configuration files for data and appearance.
  • Generate a plot:
    bash

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    circos -conf my_config.conf


Step-by-Step Guide

Step 1: Prepare Your Data

1. Obtain genomic data in formats like GFF, BED, or BAM.
2. Validate your data using scripts:
   bash

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   awk '$3 != "gene" {next} {print $0}' input.gff > output.gff


Step 2: Choose a Visualization Tool

Select a tool based on your needs:

• Linear Browsers (e.g., IGV, JBrowse) for detailed inspection.
• Circular Browsers (e.g., Circos) for relationship visualization.

Step 3: Visualize Using a Script

Python Example: Visualize GFF Data

Unix Example: Filter and Plot Data

Perl Example: Parse GFF

Step 4: Customize Tracks

• Modify configuration files (e.g., JBrowse’s trackList.json or Circos’ .conf).
• Add annotation, expression, or variant data as new layers.

Step 5: Export Results

Export visualizations to use in presentations or publications:

• IGV: Save images directly.
• Circos: Export high-quality PNG or SVG.

Conclusion

Visualization tools like IGV, UCSC Genome Browser, JBrowse, and Circos provide diverse ways to explore genomic data. By following this guide, you can start analyzing your own data and generate meaningful visualizations, supporting research in genomics, diagnostics, and beyond.