RNA-seq Metadata Application

🌳 Branching Strategy

We follow Git branching best practices to streamline collaboration and ensure code stability:

1. Main Branch

• main → Stable, production-ready code.
• Only thoroughly tested and reviewed code is merged here.

2. Development Branch

• dev → For testing and integrating new features.
• Developers merge their feature branches into dev for integration testing.

3. Feature Branches

• Feature branches are created for each new feature or bug fix.

Naming Convention:

• Use the following naming patterns:
  • feature/<feature-name>
  • bugfix/<bug-description>

Examples:

• Feature Branch:
  feature/forms

• Bug Fix Branch:
  bugfix/fix-api-error

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4. Workflow Example

1. Create a Feature Branch

git checkout -b feature/forms

#Commit Changes
git add .
git commit -m "Add metadata input form"

# Merge into Dev
git checkout dev
git merge feature/forms

# Test and Push Changes
git push origin dev

# Merge Dev into Main (after review)
git checkout main
git merge dev
git push origin main

🚀 Branch Naming Guidelines

• Use lowercase letters and hyphens for readability.
• Use descriptive names that indicate the task.

Branch Type	Naming Convention	Example
Feature	feature/<feature-name>	feature/user-authentication
Bug Fix	bugfix/<bug-description>	bugfix/fix-login-error
Hotfix (urgent)	hotfix/<urgent-fix>	hotfix/security-vulnerability
Release	release/<version-number>	release/v1.0.0

🚀 For Frontend Developer

1. Test Endpoints via Postman or Curl

Add Sample:

curl -X POST "http://localhost:8000/metadata/add-sample?sample_id=sample123&name=RNA+Sample&organism=Homo+sapiens&library_type=Paired-End"

Add Sample:

curl -X GET "http://localhost:8000/metadata/fetch-samples"

2. Update Frontend Services

• Form Integration:

  • Connect forms to /metadata/add-sample for sample submission.

• Dynamic Data Rendering:

  • Populate tables or lists using data fetched from /metadata/fetch-samples.

1. What Works? 🚀

✅ Backend

• Python-based backend using FastAPI.
• RDF data creation and insertion into GraphDB.
• Queries to fetch RDF data from GraphDB.
• Successfully stored and retrieved sample metadata in RDF format.

✅ Frontend

• React app built with Vite.
• Dev server running and serving the app at http://localhost:5173.
• Environment set up for API calls and dynamic data rendering.

✅ Database (GraphDB)

• Installed and running on http://localhost:7200.
• Repository (mesyto_repo) created and operational.
• SPARQL queries executed successfully to check data in both default and named graphs.
• Schema and sample data inserted and verified in RDF format.

✅ RDF Utilities

• Functions to create RDF data models using rdflib.
• Stored RDF data using SPARQLWrapper and requests.
• Fetch and query operations work seamlessly with GraphDB.

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2. Technologies Used ⚙️

Backend:

• Python (v3.10+)
• FastAPI - Web framework for backend APIs.
• rdflib - RDF data processing.
• SPARQLWrapper - Querying RDF databases.
• requests - HTTP communication with GraphDB.

Frontend:

• React - Frontend framework.
• Vite - Build tool for fast development.
• Axios - HTTP requests to backend APIs.

Database:

• GraphDB - Triple store database for RDF storage and queries.

Environment Management:

• Virtualenv - Python dependency isolation.
• Node.js + npm - JavaScript package management.

Security Tests:

• Environment structured for future penetration tests and upload restrictions.
• Endpoints secured with validation utilities and input sanitization.

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3. Getting Started 🛠️

Prerequisites

• Python 3.10+ installed.
• Node.js (v16+) and npm (v8+) installed.
• GraphDB Desktop Edition or Server Edition installed and running.

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1. Clone Repository:

git clone git@github.com:yourusername/metomics.git
cd mesyto.owl

2. Backend Setup:

cd backend
python3 -m venv .venv
source .venv/bin/activate   # Linux/MacOS

pip install -r requirements.txt
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

3. Frontend Setup:

cd frontend
npm install
npm run dev

4. GraphDB Setup 🗄️

1. Launch GraphDB
   Open GraphDB by navigating to:
   http://localhost:7200

2. Create a Repository

   • Go to the Repositories tab.
   • Click Create new repository.
   • Select the Repository Type (e.g., GraphDB-SE).
   • Set the Repository ID to mesyto_repo.
   • Click Create to finalize.

3. Verify the Repository
   Ensure the repository is accessible at:
   http://localhost:7200/repositories/mesyto_repo