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This study introduces a software development workflow to improve reproducibility and collaboration in laboratory research. By using GitHub, researchers can better organize experiments, document data, and ensure reproducible software environments.

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Area of Science:

  • Molecular Biology
  • Computational Biology
  • Scientific Workflow Management

Background:

  • Laboratory research faces challenges in reproducibility and data sharing, particularly in early stages.
  • Existing solutions for integrating reproducibility into research workflows are limited.
  • Modern software development practices offer potential solutions for scientific research.

Purpose of the Study:

  • To propose and demonstrate a framework for enhancing reproducibility and collaboration in laboratory research.
  • To adapt the GitHub platform for organizing and documenting the entire research project lifecycle.
  • To provide a practical, three-step approach for integrating GitHub into molecular biology lab workflows.

Main Methods:

  • Utilizing GitHub issues and project boards for experimental design and organization.
  • Implementing version control systems for documenting experiments and data analyses.
  • Employing containerized packages to ensure reproducible software environments for data analysis and writing.

Main Results:

  • Demonstrated the effective adaptation of GitHub for comprehensive research project management.
  • Outlined a scalable, versatile, and affordable three-step integration approach.
  • Provided example repositories for practical implementation.

Conclusions:

  • Adopting a software development workflow, specifically using GitHub, can significantly enhance research reproducibility and collaboration.
  • This framework is suitable for diverse research settings, from small groups to large collaborations.
  • Early adoption of this approach improves knowledge transfer efficiency and fidelity within and across laboratories.