Tips for Reproducible Research

Go to Erin's Lab meeting slides on this topic

Here are some links to useful tutorial sites on the topic

Using Git

We have a very basic overview of how to use git here.

Jenny Bryan's Happy Git with R book is a super comprehensive book (still in draft form) that details how to use git for an R analysis project using the helper tools in rstudio. (find it here)

For organising a python based analysis project. Check out this repo for tips (https://github.com/uwescience/shablona)

Linking files

One way to cut down on the size of use of hard disk space, and to keep a nicer record of where your data is coming from is to create symbolic links instead of copying files. Here's some extra information on how to do that.

• this Youtube video
• this online tutorial
• lndir (man page here) will let you create a "shadow" directory tree made entirely of symbolic links

BIDS and BIDS apps

These papers do an excellent job of explaining the motivation behind these and how to use them.

• Gorgolewski, Krzysztof J., Tibor Auer, Vince D. Calhoun, R. Cameron Craddock, Samir Das, Eugene P. Duff, Guillaume Flandin, et al. 2016. “The Brain Imaging Data Structure, a Format for Organizing and Describing Outputs of Neuroimaging Experiments.” Scientific Data 3 (June):160044. (https://www.nature.com/articles/sdata201644)
• Gorgolewski, Krzysztof J., Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capotă, M. Mallar Chakravarty, Nathan W. Churchill, et al. 2017. “BIDS Apps: Improving Ease of Use, Accessibility, and Reproducibility of Neuroimaging Data Analysis Methods.” PLoS Computational Biology 13 (3):e1005209.(http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005209)

For the current versions of the BIDS specification files see (http://bids.neuroimaging.io/).

Bookdown and R markdown for R

Erin highly recommends using R markdown and using the tool bookdown for R projects.