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Microbench: automated metadata management for systems biology benchmarking and reproducibility in Python.

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  • 1Department of Biochemistry, Vanderbilt University, Nashville, TN 37232, USA.

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Summary

Reproducibility in computational systems biology is challenging due to complex software dependencies and diverse environments. Microbench is a Python package that automates metadata capture, simplifying the tracking of software versions and hardware for reliable analysis.

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Area of Science:

  • Computational systems biology
  • Bioinformatics
  • Scientific computing

Background:

  • Computational systems biology analyses rely on multiple software packages with dependencies, often executed across heterogeneous computing environments.
  • Differences in performance and reproducibility can arise from these complex setups.
  • Current methods for capturing essential metadata, such as package versions and hardware details, are repetitive and difficult to manage centrally, even with containerization.

Purpose of the Study:

  • To address the challenges of reproducibility in computational systems biology.
  • To introduce a streamlined method for capturing and managing analysis metadata.
  • To ensure the reliability and verifiability of computational experiments.

Main Methods:

  • Development of Microbench, a simple and extensible Python package.
  • Automation of metadata capture, including execution time, software package versions, environment variables, hardware information, and Python version.
  • Utilizing plugins for enhanced functionality and flexibility.
  • Storing captured metadata in files or a Redis database.

Main Results:

  • Microbench successfully automates the capture of diverse metadata critical for reproducibility.
  • The package facilitates benchmarking of code execution and examination of environment metadata.
  • Case studies demonstrate the practical application of Microbench in ensuring reliable computational analyses.
  • Metadata capture is simplified, reducing repetitive coding efforts.

Conclusions:

  • Microbench provides an effective solution for enhancing reproducibility in computational systems biology.
  • Automated metadata capture is essential for tracking and verifying scientific computations.
  • The package simplifies the process of documenting computational environments for future reference and replication.