Tips for managing code as a researcher in life sciences
The molecular biology lab is becoming increasingly data driven and as a researcher or manager we need to make sure we're recording our work properly. Good documentation is critical to the future usability of the code, and especially so when it comes to handing a project over between project leads. It is also good practice to enable other researchers to run and use the code after publication. So here are my recommendations as a researcher and manager of a small bioinformatics team: Use GitHub, GitLab, CodeBerg or another central repository to record changes made to code daily. Team members should invite manager and colleagues as collaborators on the Git repositories. R scripts should be written as R Markdown files, as this enables a few benefits like better documentation, outputs are arranged in sequence and high level transparency. R Markdown scripts are output as HTML files for sharing/archiving. For python based workflows, Jupyter notebooks achieve more or less the same thing. Q...