https://github.com/ayoisio/variant-agents
Variant Agents: Multi-Agent Genomic Analysis
https://github.com/ayoisio/variant-agents
adk bigquery clinvar gemini gke gnomad google-cloud multi-agent-systems variant-analysis vep
Last synced: about 1 month ago
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Variant Agents: Multi-Agent Genomic Analysis
- Host: GitHub
- URL: https://github.com/ayoisio/variant-agents
- Owner: ayoisio
- License: apache-2.0
- Created: 2025-09-23T13:34:10.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2026-02-13T14:17:08.000Z (4 months ago)
- Last Synced: 2026-02-13T16:18:34.746Z (4 months ago)
- Topics: adk, bigquery, clinvar, gemini, gke, gnomad, google-cloud, multi-agent-systems, variant-analysis, vep
- Language: TypeScript
- Homepage: https://variant-agents.io
- Size: 2.12 MB
- Stars: 14
- Watchers: 0
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Multi-Agent Variant Analysis
Enterprise-grade genomic variant analysis powered by Google Cloud and Gemini
## 🚀 Overview
A production-ready platform that transforms whole-genome variant analysis from a hours-long manual process into an intelligent, conversational experience. Built with Google's Agent Development Kit (ADK) and deployed on Google Kubernetes Engine (GKE), this system processes millions of variants through a sophisticated multi-agent pipeline.
### Key Capabilities
- **🔬 Comprehensive Analysis**: Process 7.8M+ variants from whole-genome VCF files
- **🤖 AI-Powered Insights**: Natural language interface for complex genomic queries
- **⚡ Optimized Performance**: VEP annotation in ~60 minutes (vs 6+ hours standard)
- **🌍 Population Context**: Integrated gnomAD frequencies across multiple ancestries
- **📊 Clinical Assessment**: Automated pathogenicity evaluation and gene-disease associations
- **💬 Conversational Interface**: Ask follow-up questions about specific genes instantly
## ✨ Features
### For Clinicians & Researchers
- **Natural Language Processing**: Chat with your genomic data like you would with a colleague
- **Background Processing**: Submit jobs and return later - analysis continues automatically
- **Instant Queries**: Once processed, get answers about specific genes in seconds
- **Population Insights**: Compare variants against global population frequencies
- **Clinical Prioritization**: Automatic identification of pathogenic variants
### For Developers & IT Teams
- **Scalable Architecture**: Kubernetes-native design with auto-scaling
- **Multi-Agent System**: Modular pipeline with specialized agents for each task
- **Production Ready**: HTTPS support, authentication, and monitoring built-in
- **Cost Optimized**: Efficient resource usage with on-demand scaling
- **Open Source**: Fully customizable and extensible
## 🏗️ Architecture
### Technology Stack
#### Frontend (`/frontend`)
- **Framework**: Next.js 14 with App Router
- **UI**: React + TypeScript + Tailwind CSS
- **Components**: Shadcn/ui component library
- **Auth**: Firebase Authentication
- **Real-time**: Server-Sent Events (SSE)
#### Backend (`/backend`)
- **Framework**: FastAPI + Python 3.10
- **AI/ML**: Google ADK + Gemini API
- **Genomics**: VEP 113 + ClinVar + gnomAD
- **Infrastructure**: GKE + Cloud Tasks + Firestore
- **Storage**: Google Cloud Storage + BigQuery
## 🚦 Quick Start
### Prerequisites
- Google Cloud Project with billing enabled
- `gcloud` CLI installed and configured
- Docker installed
- Node.js 18+ and Python 3.10+
### Local Development
1. **Clone the repository**
```bash
git clone https://github.com/ayoisio/variant-agents.git
cd variant-agents
```
2. **Set up the frontend**
```bash
cd frontend
npm install
cp .env.example .env.local
# Configure your Firebase and API settings
npm run dev
```
3. **Set up the backend**
```bash
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
```
4. **Access the application**
- Frontend: http://localhost:3000
- Backend API: http://localhost:8080
### Production Deployment
See [backend/README.md](backend/README.md) for detailed GKE deployment instructions.
## 🎯 Usage Workflow
### 1. Start Analysis
```javascript
// Simply provide a VCF file path in natural language
"Please analyze gs://genomics-data/patient123.vcf"
"Check gs://bucket/sample.vcf for cardiac variants"
```
### 2. Background Processing (~60-70 min)
- VCF parsing and validation
- VEP annotation with consequence prediction
- gnomAD population frequency queries
- ClinVar pathogenicity assessment
### 3. Get Results
```javascript
// Ask for your report when ready
"Is my analysis complete? Please provide the report."
```
### 4. Interactive Queries
```javascript
// Ask specific questions instantly
"Were any pathogenic variants found in the BRCA1 gene?"
"Show me all variants with AF < 0.01"
"List cardiac-related findings"
```
## 📊 Performance Metrics
| Operation | Time | Throughput |
|-----------|------|------------|
| VCF Parsing | ~30 sec | 7.8M variants |
| VEP Annotation | ~60 min | 130K variants/min |
| gnomAD Query | ~30 sec | 10K variants |
| Clinical Assessment | ~2 min | 2K pathogenic variants |
| Gene Query | <5 sec | Instant |
## 🔒 Security & Compliance
- **Authentication**: Firebase Authentication with JWT tokens
- **Authorization**: Role-based access control (RBAC)
- **Data Encryption**: TLS 1.3 in transit, AES-256 at rest
- **Audit Logging**: Comprehensive activity tracking
- **HIPAA Ready**: Architecture supports HIPAA compliance requirements
## 📄 License
This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- [Google Agent Development Kit](https://github.com/google/adk-python) for the multi-agent framework
- [Ensembl VEP](https://www.ensembl.org/vep) for variant annotation
- [gnomAD](https://gnomad.broadinstitute.org/) for population frequencies
- [ClinVar](https://www.ncbi.nlm.nih.gov/clinvar/) for clinical significance
## 📧 Contact
For questions, issues, or collaboration opportunities:
- Open an [Issue](https://github.com/ayoisio/variant-agents/issues)
- Email: ayoad@google.com
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