PrioVar is a cutting-edge bioinformatics application tailored for genetic research centers. It boasts a suite of advanced features including variant prioritization, leveraging a novel machine learning scoring system, and comprehensive variant annotation. PrioVar integrates unique LLM features; one utilizes RAG for searching the PubMed database, while another facilitates knowledge graph retrieval from the Neo4j database. This robust platform is engineered to streamline data analysis processes, utilizing state-of-the-art container technology and a potent mix of backend services, making it a powerhouse for genetic data management and research.
To set up PRIOVAR using Docker, follow these steps to build and run the services:
In the project's root directory, execute the following commands to build and start the services:
docker-compose build
docker-compose up
Once the services are up, you can access the PRIOVAR platform through your browser:
- Frontend: https://localhost:3000
- Flask API: https://localhost:5000
- Spring Boot: https://localhost:8080
- Neo4j Database: Bolt port at
7687
To stop and remove all running services, use the following command:
docker-compose down
For manual installation, follow the step-by-step guide below to set up each component of the PRIOVAR system.
- Navigate to
frontend_cs491_org
:-
Ensure all necessary modules are installed:
yarn install
-
This might take a few minutes. Once the installation is complete, start the frontend server:
yarn start
-
The frontend will now be running at https://localhost:3000.
-
- Prepare the Neo4j Graph Database:
- Ensure Neo4j is Running: Before proceeding with the following steps, verify that the Neo4j Graph Database is up and operational.
- Update Configuration Settings:
- In the Flask application, update the username and password information in
config.py
. - In the Spring Boot application, modify the username and password details in
application.properties
.
- In the Flask application, update the username and password information in
- Start the Spring Boot Server:
- Navigate to the
backend
directory and follow the instructions specific to Spring Boot to get the server running.
- Navigate to the
- Set Up the Flask Server + Python Environment:
-
Navigate to the
flask
directory. -
Create a Python virtual environment and activate it:
python -m venv venv source venv/bin/activate
-
Install the necessary libraries:
pip install -r requirements.txt
-
Run
app.py
to start the Flask application:python app.py
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After executing this step, you can log in to the system using any actor available on the Neo4j Graph Database.
-