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Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software.

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Bioinformatics software development is challenging for beginners. Bionitio is a new tool that automates project setup, promoting best practices and improving software quality for researchers.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Software Engineering

Background:

  • Bioinformatics software is often developed ad hoc, leading to poor quality, limited scalability, and reproducibility issues.
  • Beginners face a high barrier to entry in bioinformatics software development, hindering the adoption of best practices.
  • Even experienced developers may not consistently follow best practices, exacerbating software quality problems.

Purpose of the Study:

  • To automate the creation of new bioinformatics software projects.
  • To ensure new projects adhere to recommended software development best practices from the outset.
  • To provide a learning aid for bioinformatics programmers and a template for new tools.

Main Methods:

  • Development of Bionitio, a command-line tool.
  • Automation of project scaffolding in 12 programming languages.
  • Inclusion of features such as argument parsing, error handling, testing, documentation, and containerization.

Main Results:

  • Bionitio generates functional, well-structured bioinformatics software projects with a single command.
  • The generated projects serve as working examples and templates for new tool development.
  • Key software engineering best practices are automatically incorporated into new projects.

Conclusions:

  • Bionitio lowers the barrier to entry for bioinformatics software development.
  • It facilitates the adoption of good programming practices, leading to higher-quality tools.
  • The tool benefits both developers and users through improved usability and consistency.