Rosetta: Python wrappers for Bioconductor packages via rpy2

Problem: R remains the gold standard in bioinformatics thanks to Bioconductor. However, many data scientists prefer Python for machine learning and building production. Currently, bridging tools such as rpy2 suffer a lot from stability issues. For instance, ABI symbolic linking errors and complex S4 object mapping failures, obstructing complete integration with essential tools like DESeq2. Solution: This project aims to enhance the Rosetta library by implementing a robust three-tier API architecture. This architecture includes an easy-to-use high-level Python interface, a fine-grained control layer for advanced users, and a subprocess-based fallback mechanism to prevent core crashes. I will focus on addressing deep interoperability challenges, including S4 method distribution and cross-language type conversion. Deliverables: 1.A stable, production-ready DESeq2 and edgeR Python wrapper library. 2.A three-tier API design ensuring 100% statistical consistency with native R output. 3.During periods of high load, the subroutine falls back to the backend to ensure system stability. 4.Comprehensive documentation and a Pytest-based validation suite ensure a reproducible experimental environment.