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.
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.