21  Resources

21.1 Resources for R

21.1.1 Books and Comprehensive Guides

• R for Data Science (Wickham et al. 2023) - comprehensive introduction to doing data science with R
• R Packages (Wickham and Bryan 2023) - complete guide to R package development
• Awesome R Package Development Tools - curated list of tools for R package development
• Advanced R (Wickham 2019) - deep dive into R programming and internals
• Mastering Shiny (Wickham 2021) - comprehensive guide to building web applications with Shiny
• Engineering Production-Grade Shiny Apps (Fay et al. 2021) - best practices for production Shiny applications
• Happy Git and GitHub for the useR (Bryan 2023) - guide to using Git and GitHub with R
• DataCamp - email Kristen for access

21.1.2 UC Davis DataLab Workshops and Tutorials

The UC Davis DataLab provides extensive workshops and learning materials for data science:

• Workshop Index - comprehensive catalog of all DataLab workshops
• R Basics Workshop - foundational R programming for beginners
• Research Toolkits - in-depth guides for research tools and methods
• Install Guides - setup instructions for data science software

21.1.3 Cheat Sheets

• dplyr and tidyr cheat sheet
• ggplot cheat sheet
• data table cheat sheet
• RMarkdown cheat sheet

21.1.4 Style and Best Practices

• Hadley Wickham’s R Style Guide

21.1.5 Tidy Evaluation Resources

• Tidy Eval in 5 Minutes (video)
• Tidy Evaluation (e-book)
• Data Frame Columns as Arguments to Dplyr Functions (blog)
• Standard Evaluation for *_join (stackoverflow)
• Programming with dplyr (package vignette)

21.2 Resources for Git & Github

• Happy Git and GitHub for the useR (Bryan 2023) - comprehensive guide to using Git and GitHub with R
• GitHub Skills: Introduction to GitHub
• UC Davis DataLab Git Sandbox - hands-on Git practice repository

21.3 Resources for Python

• UC Davis DataLab Python Basics Workshop - foundational Python programming
• Natural Language Processing with Python - text analysis and NLP techniques

21.4 Resources for Julia

• UC Davis Julia Users Group Julia Basics Workshop - foundational Julia programming

21.5 Scientific figures

• Ten Simple Rules for Better Figures (Rougier et al. 2014)

21.6 Writing

• Unpacking the Scientific Toolbox (Silbiger and Stubler 2019)
• ICMJE Definition of authorship (International Committee of Medical Journal Editors, n.d.)
• Computational science: …why scientific programming does not compute (Merali and Giles 2010)
• The Pathway to Publishing: A Guide to Quantitative Writing in the Health Sciences
• Principles of Scientific Writing - a handbook covering scientific writing principles including citations and evidence, word choice, and conciseness
• Secret, actionable writing tips

21.7 Presentations

• How to tell a compelling story in scientific presentations (Van Noorden 2021)
• How to give a killer narratively-driven scientific talk
• How to make a better poster
• How to make an even better poster

21.8 Professional advice

• Professional advice, especially for your first job
• Team Public Health Substack

21.9 Funding

• Building Your Funding Train
• NIH Grant Writing Resources

21.10 Ethics and global health research

• Global Code of Conduct For Research in Resource-Poor Settings
• Addressing power asymmetries in global health (Abimbola et al. 2022)
• Transforming Global Health Partnerships

Abimbola, Seye, Sheena Asthana, Cristina Montenegro, et al. 2022. “Addressing Power Asymmetries in Global Health: Imperatives in the Wake of the COVID-19 Pandemic.” PLOS Global Public Health 2 (10). https://doi.org/10.1371/journal.pgph.0002269.

Bryan, Jennifer. 2023. Happy Git and GitHub for the useR. https://happygitwithr.com/.

Fay, Colin, Sébastien Rochette, Vincent Guyader, and Cervan Girard. 2021. Engineering Production-Grade Shiny Apps. Chapman; Hall/CRC. https://doi.org/10.1201/9781003029878.

International Committee of Medical Journal Editors. n.d. “Defining the Role of Authors and Contributors.” ICMJE. http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html.

Merali, Zeeya, and Jim Giles. 2010. “Computational Science: Error ... Why Scientific Programming Does Not Compute.” Nature 467: 775–77. https://doi.org/10.1038/467775a.

Rougier, Nicolas P., Michael Droettboom, and Philip E. Bourne. 2014. “Ten Simple Rules for Better Figures.” PLOS Computational Biology 10 (9). https://doi.org/10.1371/journal.pcbi.1003833.

Silbiger, Nyssa J., and Ariel D. Stubler. 2019. “Unpacking the Scientific Toolbox: Five Skills for the Modern Scientist.” Nature, ahead of print. https://doi.org/10.1038/d41586-019-02918-5.

Van Noorden, Richard. 2021. “Scientists and Science Communicators Swap Tips on How to Tell Compelling Stories.” Nature, ahead of print. https://doi.org/10.1038/d41586-021-03603-2.

Wickham, Hadley. 2019. Advanced r. 2nd ed. Chapman; Hall/CRC. https://doi.org/10.1201/9781351201315.

Wickham, Hadley. 2021. Mastering Shiny. O’Reilly Media. https://mastering-shiny.org/.

Wickham, Hadley, and Jennifer Bryan. 2023. R Packages. 2nd ed. O’Reilly Media. https://r-pkgs.org/.

Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science. 2nd ed. O’Reilly Media. https://r4ds.hadley.nz/.