Bionitio, towards best practice in bioinformatics software
Published: 23 September 2019
Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software
Peter Georgeson, Anna Syme, Clare Sloggett, Jessica Chung, Harriet Dashnow, Michael Milton, Andrew Lonsdale, David Powell, Torsten Seemann, Bernard Pope
Bioinformatics software tools are often created ad hoc, frequently by people without extensive training in software development. In particular, for beginners, the barrier to entry in bioinformatics software development is high, especially if they want to adopt good programming practices. Even experienced developers do not always follow best practices. This results in the proliferation of poorer-quality bioinformatics software, leading to limited scalability and inefficient use of resources; lack of reproducibility, usability, adaptability, and interoperability; and erroneous or inaccurate results.
Bionitio is a tool that automates the process of starting new bioinformatics software projects following recommended best practices. With a single command, the user can create a new well-structured project in 1 of 12 programming languages. The resulting software is functional, carrying out a prototypical bioinformatics task, and thus serves as both a working example and a template for building new tools. Key features include command-line argument parsing, error handling, progress logging, defined exit status values, a test suite, a version number, standardised building and packaging, user documentation, code documentation, a standard open source software license, software revision control, and containerisation.
- for beginner-to-intermediate bioinformatics programmers
- as an excellent starting point for new projects
- to help developers adopt good programming practices from the beginning of a project
- for encouraging high-quality tools to be developed more rapidly
- for enabling tools to be more easily installed and used in a consistent way.
Bionitio is released as open source software under the MIT License and is available at https://github.com/bionitio-team/bionitio.
Congratulations to a great team from Melbourne Bioinformatics and close colleagues in our networks who collaborated on this truly community-focussed project.