HumanDNAVisualizer

Exploring genomic data through interactive 3D visualization and evidence-labeled biological models

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Important Disclaimer

HumanDNAVisualizer is an educational and research-oriented visualization platform.

It does NOT:

• Provide medical diagnoses
• Predict disease outcomes
• Recommend treatments or lifestyle changes
• Replace professional medical advice

All visualizations, mappings, and AI-generated explanations are informational, non-diagnostic, and explicitly labeled with uncertainty and evidence levels.

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Screenshots

Application Overview

HumanDNAVisualizer - Interactive 3D anatomy visualization with genomic variant overlays, data import dashboard, and educational learn mode

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Overview

HumanDNAVisualizer is a local-first, open-source platform that enables individuals, researchers, and educators to explore genomic, phenotypic, and environmental data through interactive 3D visualizations and transparent biological mapping models.

The project emphasizes:

• Scientific honesty over overclaiming
• Vendor-neutral data compatibility
• Evidence-labeled associations
• Privacy-first, offline-capable architecture

Rather than producing clinical conclusions, HumanDNAVisualizer focuses on making complex biological data visible, navigable, and explainable.

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What Makes HumanDNAVisualizer Different?

Unlike proprietary tools or black-box analytics platforms, HumanDNAVisualizer:

• Visualizes biological associations instead of diagnosing
• Labels uncertainty and evidence levels
• Separates data, logic, and interpretation
• Processes data locally by default
• Supports learning, research, and exploration
• Avoids vendor lock-in, proprietary SDKs, and ToS violations

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Key Features

• Data Import (User-Provided)

  • Genomic variants (VCF, generic genotype TSV/CSV)
  • Phenotypic records (FHIR-compatible JSON)
  • Environmental and lifestyle data (CSV)

• 3D Visualization

  • Interactive 3D models (Three.js)
  • Organ and system highlighting
  • Layered overlays with evidence labels

• Evidence-Labeled Biological Mapping

  • Variant → pathway → system associations
  • Explicit certainty levels (High / Medium / Low)
  • Source references for supported biology

• AI-Assisted Explanations

  • Natural-language summaries of what is being visualized
  • No autonomous conclusions or prescriptions
  • Clear labeling of AI-generated content

• Privacy & Security

  • Local-first processing
  • Encryption at rest
  • No default cloud uploads

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Supported Data Formats

Genomic Data

HumanDNAVisualizer provides vendor-neutral import capabilities for genomic variant data. The platform supports flexible column mapping and validation for various file formats:

• VCF (Variant Call Format) - .vcf and .vcf.gz

  • Supports VCF 4.x standard format
  • Extracts chromosome, position, rsID, reference/alternate alleles, quality scores, and genotypes
  • Automatic genome build detection from header metadata
  • Strict and lenient validation modes

• Generic Genotype Files - TSV or CSV format

  • Flexible column naming (e.g., rsid/snp/variant, chromosome/chrom/chr, position/pos)
  • Supports genotype formats: AA, AG, A/G, A|G
  • Can use either combined genotype column or separate allele columns
  • Automatic delimiter detection (tab or comma)

Import Features:

• Row-level error reporting with line numbers
• SHA-256 file hashing for integrity verification
• Provenance tracking (parser version, import timestamp, source format)
• Configurable validation (strict mode fails on first error; lenient mode collects all errors)

Users are responsible for ensuring they have the right to use and process uploaded genetic data. All imports are for educational and research purposes only.

Phenotypic Data

• FHIR R4-compatible JSON

Environmental Data

• CSV / JSON

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Architecture Overview

HumanDNAVisualizer/
├── backend/
├── frontend/
├── ai-service/
├── llm-service/
├── database/
├── spec/
└── .claude/

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Tech Stack

Layer	Technology
Frontend	React 18, Three.js
Backend	Java 17, Spring Boot
AI Services	Python 3.10, FastAPI
Database	PostgreSQL / SQLite
Infrastructure	Docker

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Quick Start

Prerequisites

• Java 17 or higher
• Node.js 18 or higher
• Maven 3.8+
• 8GB RAM minimum (for development)

Start Demo Mode (Fastest Way)

Windows:

start-demo.bat

Linux/Mac:

./start-demo.sh

This will start:

• Backend API on http://localhost:8081
• Frontend on http://localhost:3000
• AI Model Service on http://localhost:8000

Demo Users (auto-created):

• Username: demo / Password: demo123 (USER)
• Username: admin / Password: admin123 (ADMIN)
• Username: moderator / Password: mod123 (MODERATOR)

Manual Setup

1. Start Backend:

cd backend/dna-integrator
mvn spring-boot:run -Dspring-boot.run.profiles=dev

2. Start Frontend:

cd frontend
npm install
npm run dev

3. Access the Application:

• Frontend: http://localhost:3000
• Swagger UI: http://localhost:8081/swagger-ui.html
• H2 Database Console: http://localhost:8081/h2-console

First Steps

1. Login with demo credentials at http://localhost:3000
2. Upload genomic data (VCF or TSV file)
3. View 3D anatomy visualization with variant overlays
4. Try Learn Mode for guided educational tours

For detailed setup instructions, see QUICK-START-DEMO.md

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Legal & Licensing

• License: AGPL-3.0-or-later (GNU Affero General Public License v3.0 or later)
• Copyright: Cornmeister LLC
• Contact: sekacorn@gmail.com
• No proprietary SDKs or datasets
• Vendor-neutral file format compatibility

See LICENSE file for complete terms.

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HumanDNAVisualizer exists to make biology visible — not to replace human judgment.