Tips for reproducible research

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.