3 Code
All data processing and analysis should be performed with code (i.e., avoid spreadsheets), and all code should be packaged in scripts that are version controlled and follow a style guide. Using code and scripts allows for better organization, documentation, and reproducibility of analysis workflows. All emLab code should be stored in the emLab GitHub account.
Recommended readings:
Bryan, Jennifer. 2018. “Excuse Me, Do You Have a Moment to Talk About Version Control?” The American Statistician 72 (1): 20–27. https://doi.org/10.1080/00031305.2017.1399928.
Stodden, Victoria, and Sheila Miguez. 2014. “Best Practices for Computational Science: Software Infrastructure and Environments for Reproducible and Extensible Research.” Journal of Open Research Software 2 (1): e21. https://doi.org/10.5334/jors.ay.
Wilson, Greg, D. A. Aruliah, C. Titus Brown, Neil P. Chue Hong, Matt Davis, Richard T. Guy, Steven H. D. Haddock, et al. 2014. “Best Practices for Scientific Computing.” PLOS Biology 12 (1): e1001745. https://doi.org/10.1371/journal.pbio.1001745.
Wilson, Greg, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, and Tracy K. Teal. 2017. “Good Enough Practices in Scientific Computing.” PLOS Computational Biology 13 (6): e1005510. https://doi.org/10.1371/journal.pcbi.1005510.