scienceparkstudygroup / dual-luciferase Goto Github PK

To go from data .csv or .tsv into an R object that can be used to normalise to reference gene

If data could be placed into their own data/ folder in an open format, it would be a great improvement.

To promote openness (not everyone is using Excel), input data could be saved into two .tsv (tabulated separated values) or .csv (comma separated values). It is also nice to abide by this open format since it is well rendered online on GitHub (see below).

https://help.github.com/en/github/managing-files-in-a-repository/rendering-csv-and-tsv-data

I recommend removing install.packages from R-code, since it is needed only once

I'll make some changes that can help with reproducibility, coding style, etc.

Sources of inspiration:

• SWC

  • Structure your project folder
  • Make your code readable: code with intention (explain "why" and not "how")
  • Make your code modular: write functions in an external file (functions.R) and source() them
  • Divide your code into steps: ideally one step = one function sourced
  • Test the functions
  • Abide to a coding style: for instance https://style.tidyverse.org/

• eScience Center Handbook

I think it is a good idea to change the stats to either mean or median