  Unorganized heaps of analysis code are a growing liability as data analysis
pipelines are getting longer and more complicated. This is worrying, as
neuroscience papers are getting retracted due to programmer error. In this
paper, some guidelines are presented that help keep analysis code well
organized, easy to understand and convenient to work with:
  1. Each analysis step is one script
  2. A script either processes a single recording, or aggregates across
recordings, never both
  3. One master script to run the entire analysis
  4. Save all intermediate results
  5. Visualize all intermediate results
  6. Each parameter and filename is defined only once
  7. Distinguish files that are part of the official pipeline from other
scripts
  In addition to discussing the reasoning behind each guideline, an example
analysis pipeline is presented as a case study to see how each guideline
translates into code.
