BCM HGSC Hackathon
“Innovation distinguishes between a leader and a follower.” - Steve Jobs
Introduction
In October 2022, I participated remotely in the BCM_HGSC Hackathon, where I focused on developing and optimizing MetScale, an open-source tool for querying genomic databases.
Progress
Initial Setup
My initial task was to understand the existing codebase and identify potential areas for optimization. The tool was initially set up for basic data retrieval but required enhancements for efficiency and scalability.
Code Optimization
I restructured the Python code to improve its performance and maintainability. This included refining the database queries and integrating more robust error handling mechanisms.
Documentation and Testing
Using Jupyter Notebooks, I documented the entire process, providing clear examples and instructions for future users. I also developed test cases to ensure the tool’s reliability.
Results
The optimization efforts resulted in a significant improvement in query execution times and overall data handling. The tool now supports more complex queries and can handle larger datasets efficiently. Explore the final tool and its capabilities here.
Technology Learned/Used
This project allowed me to deepen my expertise in several areas:
- Python for backend development
- SQLite for efficient data management
- Jupyter Notebooks for documentation and presentation
Conclusion
The BCM_HGSC Hackathon was a valuable experience in applying practical coding skills to real-world genomic research challenges. The enhancements made to the MetScale tool not only improved its performance but also contributed to its potential application in genomic studies.
