🦠 AMR Genome Analyzer

Automated Antimicrobial Resistance Profiler for Bacterial Genomes
Professional Bioinformatics Pipeline developed for Forneus Technologies

🌟 Live Demo: AMR Genome Analyzer on Streamlit

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📸 Dashboard & Interface

🧬 Professional Web Interface

A sleek, glassmorphism-inspired UI designed for enterprise bioinformatics.

📊 Comprehensive AMR Dashboard & Overview

Automated detection of resistance mechanisms and key genomic metrics.

📈 Analytics & First Results Table

High-level summary of the most critical resistance findings.

📋 Detailed Resistance Genes Table

Granular data view showing exact gene locations, identities, and resistance mechanisms.

💡 Clinical Interpretation

Clear, actionable summaries for immediate medical or research decision-making.

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📌 Description

AMR Genome Analyzer is a Python command-line tool that automates the detection of antimicrobial resistance (AMR) genes in bacterial genomes. It integrates with the NCBI Entrez API to fetch GenBank records, parses standard BLAST tabular output (.tsv) filtered against the CARD (Comprehensive Antibiotic Resistance Database), and produces a professional, publication-ready visualization.

This tool is designed for:

• Veterinary microbiologists needing quick AMR profiling of pathogens (e.g., Staphylococcus aureus, E. coli)
• Researchers performing rapid genomic surveillance
• Freelance bioinformaticians delivering AMR reports to clients

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✨ Features

Feature	Description
🔬 NCBI Entrez Integration	Auto-downloads bacterial genomes by accession number (GenBank format)
🧬 BLAST Result Parsing	Reads standard -outfmt 6 TSV output, filters by identity threshold
📊 Smart Visualization	Horizontal bar chart colored by antibiotic class with mechanism labels
🎭 Demo Mode	Runs without internet/BLAST using realistic simulated S. aureus data
🧪 Full Test Coverage	10 pytest tests covering all core functions and edge cases
⚙️ Flexible CLI	argparse-based interface with --demo, --accession, --identity, --top flags

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🚀 Quick Start

1. Clone and install

git clone https://github.com/YOUR_USERNAME/amr-genome-analyzer.git
cd amr-genome-analyzer
pip install -r requirements.txt

2. Configure your email (required for NCBI)

cp .env.example .env
# Open .env and replace with your real email:
# NCBI_EMAIL=your_real_email@example.com

3. Run in demo mode (no internet needed)

python project.py --demo

4. Run with a real genome

# Default genome: Staphylococcus aureus NCTC 8325
python project.py --accession NC_007795.1

# Custom identity threshold and top-15 genes
python project.py --accession NC_007795.1 --identity 80 --top 15

5. See all options

python project.py --help

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📁 Project Structure

amr-genome-analyzer/
├── project.py          # Main program (download → filter → visualize)
├── test_project.py     # pytest unit tests (10 tests)
├── requirements.txt    # Python dependencies
├── .env.example        # Template for environment variables
├── .gitignore          # Excludes .env and cache from Git
├── data/               # Downloaded GenBank genome files (auto-created)
└── results/            # Output charts and BLAST data (auto-created)
    ├── blast_hits.tsv
    └── top_resistance_genes.png

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🧪 Running Tests

pytest test_project.py -v

Expected output: 10 passed covering:

• DataFrame generation and structure validation
• BLAST file filtering and sorting correctness
• Error handling (missing file, empty file)
• Chart file creation and empty-data handling

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📊 Output Example

The tool generates a chart like this:

• Each bar = one resistance gene
• Color = antibiotic class (red=beta-lactam, orange=tetracycline, blue=macrolide, etc.)
• % label inside bar = identity to CARD reference
• Italic text right of bar = resistance mechanism

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🔬 Scientific Background

• CARD (Comprehensive Antibiotic Resistance Database) — gold standard reference for AMR genes
• BLAST (Basic Local Alignment Search Tool) — sequence similarity search
• mecA gene — confers methicillin resistance (MRSA)
• vanA gene — glycopeptide (vancomycin) resistance
• Identity threshold ≥70% recommended for species-level hits

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💼 Future Development

• Streamlit web interface for clinical use
• Multi-genome batch processing
• PDF report generation
• Real-time BLAST API integration (NCBI BLAST+)
• Species auto-detection from genome metadata

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🛠 Dependencies

Package	Version	Purpose
biopython	≥1.81	NCBI Entrez API, SeqIO parsing
pandas	≥2.0.0	Data manipulation
matplotlib	≥3.7.0	Visualization
python-dotenv	≥1.0.0	Secure environment configuration
pytest	≥7.4.0	Unit testing

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👤 Author

Built as CS50P final project.
Domain: Veterinary bioinformatics / AMR genomics
Platform: Python 3.11+

Contact

Juliia Nuzhnenko

• Email: julia.n@forneus.io
• LinkedIn: Juliia Nuzhnenko

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