Organising yourself as a dry lab scientist · Posted: Feb 16, 2007

Browsing wikiomics, I found this small section on keeping organised as a practising bioinformatician. In particular, I found these lines very interesting:

  • Use text files/plain e-mail whenever possible.
  • Give meaningful names to your files.
  • Create separate folders/directories for each project with meaningful names.

I find keeping my work organised one of the most frustrating but necessary tasks of being a bioinformatician. Wet scientists are expected to keep laboratory books, and not doing so is considered very bad practice since it makes it near impossible for someone else to reproduce the work. I am jealous when I see these books filled with pictures of gels and printed tables of results.

I’ve tried previously to use a lab book for keeping track of my work, but I didn’t find it applicable for the many different types of scripts and results I was producing. I think in part this boils down to how little time it takes to write a new script versus the time required to put pen to paper to describe what you’ve just done. Therefore below I’m going to outline one possible method for organising myself.

First of all use the most verbose names as possible for directories and files. This helps when trying to find a specific file. Being verbose as possible in naming your files is useful because often sets of files are all related to a similar subject. Take the following example:

ancova_sequence_hydrophobicity.R
ancova_sequence_hydrophobicity_interaction_term.R
ancova_sequence_hydrophobicity_residuals.R

All three files contain a script fitting an ancova model, but all differ slighty in focusing on different parts of the model. Finding the one you need is still simple for you, but perhaps not so in a few months time when you return to the results to write a paper:

ancova_sequence_hydrophobicity.R
ancova_sequence_hydrophobicity.csv
ancova_sequence_hydrophobicity.png
ancova_sequence_hydrophobicity_interaction_term.R
ancova_sequence_hydrophobicity_interaction_term.csv
ancova_sequence_hydrophobicity_interaction_term.png
ancova_sequence_hydrophobicity_residuals.R
ancova_sequence_hydrophobicity_residuals.csv
ancova_sequence_hydrophobicity_residuals.png

This time I now have the files for the results of each model (.csv) and a plot of these results (.png). This illustrates how quickly the number of files can expand. I thinks its also more difficult to understand what each file refers to since they all have very similar names.

Here’s an alternative way I think these files could instead be organised:

ancova_sequence_hydrophobicity/
  lib/
    generate_ancova_model.r
  scripts/
    model.r
    model_interaction_term.r
    model_residuals.r
  results/
    model.csv
    model_interaction_term.csv
    model_residuals.csv
  pictures/
    model.png
    model_interaction_term.png
    model_residuals.png

Each sub directory describes its contents, which satifies the requirement for verbose naming. Furthermore the directory path contributes to describing each file, e.g. ancova_sequence_hydrophobicity/results/model_residuals.csv. This is helpful if you are referencing the file else where and want an idea of what the file contains.

Since the files are related, they each have an identically named counterpart in the other directories. This is useful for determining which script produced which result. Furthermore since I have common code I use to generate the ancova model I should extract this out into a lib directory. This means all the code for the model is in one place and therefore easier to edit and maintain.

There are an infinite number of ways to organise to organise your dry projects. My example is just one way to do this however and I think any system is better than nothing for keeping track of what you’ve been doing.

Interested in bioinformatics and data analysis? Follow me on twitter.