Here we provide additional resources that will benefit trainees who want to learn more about certain aspects of data science and computational methods discussed throughout these training modules. There are many additional resources available for learning more about data management and analysis methods. Select resources that we have found helpful are detailed below.

R Programming Resources:

  • Coursera provides online courses for many technical topics, including several on R programming.

  • Datacamp provides online courses for learning R, Python, statistics, and more.

  • R for Data Science, developed by Hadley Wickham and Garrett Grolemund, is an online resource that also comes in the format of a book, that teaches participants how to do data science using R.

  • R Graphics Cookbook, developed by Winston Chang, is a practical guide that provides more than 150 “recipes” to demonstrate generating graphics in R quickly.

  • R for Graduate Students, developed by a PhD student, Wendy Huynh, who taught herself R as a needed component of her research while obtaining a PhD and wanted to share her experience and lessons learned.

  • Reproducible Medical Research with R, developed by Dr. Higgins as an online resource for those in the medical field interested in analyzing the data to better understand health, disease, or the delivery of care.

Community Discussions on R and R Packages:

  • Stack Overflow online discussion forums.

  • Discussion forums within Bioconductor, where you can communicate directly with package developers.

R Interfaces

  • RStudio is an integrated development environment for R that is available in two formats: RStudio Desktop, a regular desktop application, and RStudio Server, a remote server that allows accessing RStudio using a web browser.

  • R Markdown is a LaTeX-like documentation format that allows users to draft comprehensive documentation throughout R-based scripts. R Markdown is advantageous in that users can run their code on their computer and save a ‘knitted’ version of the code that also displays messages, results, and graphics that result from execution of the developed script.

  • R Notebook is an R Markdown document that allows users to run independent and interactive execution of chunks of code. This interface allows users to visually assess the output as they develop a R Markdown document without having to knit the entire document in order to visualize the output.

Data Science and Statistical Analysis Resources: