rstudio2019

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Resources from my Rstudio::conf 2019 talk

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How To Make Your Data Analysis Notebooks More Reproducible

rstudio_talk_slides

Slide deck | Slide deck as PDF

πŸŽ₯ Video of talk at rstudio::conf(2019)

Resources

I have included a handful of links to papers, software packages and tutorials/manuals about some tools I mention in my talk. Pull requests or issues on additional ones to include are welcome.

Research Compendia

Examples of Research Compendia on GitHub Below are a few links to real world examples of research compendia in R. To have a minimal compendium, all you really need is a valid

DESCRIPTION
file containing a handful of fields such as type, name, version and dependencies. See Marwick et al 2017 for a detailed description of the different types of compendia.

Small - Code and data associated with Duffy, James, and Longworth Applied and Environmental Microbiology paper describing the ecology, virulence, and phylogeny of a brood parasite of Daphnia, Blastulidium paedophthorum;

Medium - Resolving the measurement uncertainty paradox in ecological management

Large

Software packages related to research compendia

  • πŸ“¦
    rrtools
    by Ben Marwick (also the author of the packaging data analysis paper mentioned above) extends functions in
    devtools
    and provides instructions, templates, and functions to make a basic compendium suitable for doing reproducible research with R.
    • Also see πŸ“¦ workflowr by John Blischak and the task view on R-based data analysis projects maintained by John Blischak, Anna Krystalli, Ben Marwick, Daniel NΓΌst.
  • πŸ“¦
    usethis
    Many of the major function in
    rrtools
    are imported from
    usethis.
    A savvy user can get by setting up and maintaining a compendium purely with
    usethis
    functions.
  • πŸ“¦
    goodpractice
    - Designed to help you build more robust packages, the package does a deep dive on your package contents and provide advice on syntax pitfalls to avoid, code formatting suggestions, and helps you improve overall package structure.
  • The πŸ“¦
    rticles
    package by JJ has numerous journal templates and together with Rstudio addins like word
    countaddin
    and
    citr
    +
    knitcitations
    .

πŸ“ˆ Data management

  • πŸ“¦
    piggyback
    , [docs]: This clever R package allows you to attach arbitrary data (or other) files (upto 2gb each) to a GitHub release. Given GitHub's fast CDN, this would be an easy way to quickly attach large files to a compendium and read them back in a local/collaborator/remote environment very easily. As always be sure to archive a long-term copy on Zenodo.
  • πŸ“¦
    arkdb
    [docs]: This package allows you to archive and unarchive databases as flat text files.
  • πŸŽ₯ For more on setting up data packages, see this excellent talk by Noam Ross at New York R.

Computational environments: Binder and friends

Other hosted Binder hubs

Setting up Binder for your analysis

I have captured all the various ways to set up mybinder with a R project in a separate document.

Are you interested in setting up or hosting a binderhub for the R community? Get in touch via the issues.

Also see - Whole Tale - Computing environments for reproducibility: Capturing the β€œWhole Tale” - OA paper describing the Whole Tale project. - Code Ocean - A commercial, blackbox, full-stack service that will accomplish something similar to the above two projects. Code Ocean links will likely start appearing in papers soon.

Software packages related to setting up computational environments

  • πŸ“¦
    Containerit
    . Detailed blog post This sweet package will generate a Dockerfile for you by examining the code inside a folder or just from your session info. This is analogous to
    repo2docker
    but is very R centric
  • stevedore
    Although there are a few docker clients (docker, harbor), this is my recommendation for managing docker containers from inside R.

πŸ”¨ Workflows: drake and friends

  • πŸ“¦
    drake
    - An R-focused pipeline toolkit for reproducibility and high-performance computing. Install the package from here or CRAN.
  • The prequel to the drake R package A blog post by the creator of drake describing his motivation for the package.
  • drake manual A detailed
    bookdown
    guide on how to setup and use drake for projects of varying levels of complexity.
  • Presentation on drake Slides from a talk by Will Landau (who is here at the conference so go pick his brain if you want to learn more!)

Real world drake examples - Pathogen modeling study

Miscellaneous - IKEA diagram inspired by IDEA instructions


Acknowledgments

Many thanks to Chris Holdgraf, Carl Boettiger, Will Landau, and Ben Marwick for various discussions on these topics. Also thanks to Ciera Martinez, Kara Woo, and Nick Tierney for comments on the presentation.

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