OPEN Source code for biology and medicine | 2 Mar 2013
Background Reproducibility is the hallmark of good science.Maintaining a high degree of transparency in scientific reporting isessential not just for gaining trust and credibility within thescientific community but also for facilitating the development of newideas. Sharing data and computer code associated with publications isbecoming increasingly common, motivated partly in response to datadeposition requirements from journals and mandates from funders. Despitethis increase in transparency, it is still difficult to reproduce orbuild upon the findings of most scientific publications without accessto a more complete workflow.Findings Version control systems (VCS), which have long beenused to maintain code repositories in the software industry, are nowfinding new applications in science. One such open source VCS, git,provides a lightweight yet robust framework that is ideal for managingthe full suite of research outputs such as datasets, statistical code,figures, lab notes, and manuscripts. For individual researchers, gitprovides a powerful way to track and compare versions, retrace errors,explore new approaches in a structured manner, while maintaining a fullaudit trail. For larger collaborative efforts, git and git hostingservices make it possible for everyone to work asynchronously and mergetheir contributions at any time, all the while maintaining a completeauthorship trail. In this paper I provide an overview of git along withuse-cases that highlight how this tool can be leveraged to make sciencemore reproducible and transparent, foster new collaborations, andsupport novel uses.
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