General

• ROpenSci’s Reproducibility guide

Courses

• Tools for Reproducible Research
• Reproducible and collaborative data science
• Data wrangling, exploration, and analysis with R
• Reproducible Research (part of the Johns Hopkins data science specialization at Coursera)

Books

• Dynamic documents with R and knitr
• R Markdown Cookbook
• Reproducible research with R and RStudio
• Implementing reproducible research (PDFs of chapters at ocf.io)

Karl’s tutorials

• minimal make
• knitr in a knutshell
• R package primer
• git/github guide

Organizing files and data

• Nine simple ways to make it easier to (re)use your data (paper)
• Some simple guidelines for effective data management (paper)
• Quick guide to organizing computational biology projects (paper)

Reproducible reports

• knitr
• R Markdown
• Markdown
• Jupyter notebooks

R packages

• R package primer
• Hadley Wickham’s R packages book
• Hilary Parker’s tutorial on R packages
• R package development the Leek group way
• Use of an R package to facilitate reproducible research
• rOpenSci Packages: Development, Maintenance, and Peer Review

Copyright and software/data licenses

• Victoria Stodden:
  • What computational scientists need to know about Intellectual property law (pdf)
  • The legal framework for reproducible scientific research
• Coding horror post about licenses
• The whys and hows of licensing scientific code by Jake VanderPlas
• A quick guide to software licensing for the scientist-programmer (Morin et al. PLoS Comput Biol 8:e1002598, 2012)
• Copyright basics (pdf from US Copyright Office)
• Database legal protections
• VertNet guide to copyright and licenses for dataset publication