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
• litedown: R Markdown Reimagined - a book by Yihui Xie on {litedown}, a lightweight R Markdown implementation aimed at simplicity and speed
• 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

• Data transformation with dplyr cheat sheet
• Data tidying with tidyr cheat sheet
• Data visualization with ggplot2 cheat sheet
• data table cheat sheet
• R Markdown cheat sheet

21.1.4 Style and Best Practices

• Hadley Wickham’s R Style Guide

21.1.5 Data Documentation and Dictionaries

• Tidyverse data-dict - open specification and CLI tool for creating, validating, and documenting data dictionaries in YAML format

21.1.6 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)

21.1.7 Continuous Integration for R

• r-ci: Easy and portable CI for R packages - a portable shell script by Dirk Eddelbuettel for testing R packages across GitHub Actions, Azure Pipelines, CircleCI, and local Docker environments
• r-codeberg - community organization supporting R package development and hosting on Codeberg, including the r-codeberg migration guide for porting packages from GitHub to Codeberg
• Woodpecker CI - community-driven, container-based continuous integration system that integrates with Codeberg, Forgejo, and Gitea for running automated R package checks and pipeline workflows
• shinycoreci: CI Testing for shiny - R package developed by the Posit Shiny team for testing the Shiny ecosystem across GitHub Actions runner environments

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 Learn - official interactive courses, Skills exercises, learning pathways, and credentials
• GitHub Skills: Introduction to GitHub
• UC Davis DataLab Git Sandbox - hands-on Git practice repository
• GitKraken - cross-platform Git client and developer platform with visual commit graphs, interactive rebasing, and GitKraken Kepler for agent-driven development workflows
• About stacked pull requests - official GitHub guide to breaking large changes into stacked pull request chains
• Claude Code on the Web: Auto-Fix Pull Requests - documentation on Claude Code’s web interface for automatically investigating and resolving check failures and review comments on pull requests
• Claude Code Workflows - documentation on Claude Code’s dynamic subagent orchestration feature for parallel codebase audits, migrations, and evaluations
• Google Code Review Developer Guide - comprehensive guidelines on code review standards and pull request authoring; the upstream source for the Tidyverse code review principles (see acknowledgments)

21.3 Practical Computing and Command Line

• The Missing CS Quarter at UC Davis - practical computing skills, shell tools, command-line workflows, and version control (GitLab repository)

21.4 Resources for Python

• UC Davis DataLab Python Basics Workshop - foundational Python programming
• Natural Language Processing with Python - text analysis and NLP techniques
• Jupyter Notebooks in a Git Repository - guide by Matthias Geier on managing Jupyter notebooks in Git repositories, including workflows for stripping cell outputs before committing and strategies for sharing executed notebooks

21.5 Resources for Julia

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

21.6 Artificial Intelligence & Coding Agents

• Working with AI (wai) - our lab’s comprehensive guide to AI coding agents, harnesses, policies, and workflows
• When AI builds itself: Recursive self-improvement in practice - Anthropic Institute analysis of recursive self-improvement mechanisms, AI capability trajectories, and safety considerations
• pi - minimalist, extensible AI agent toolkit providing a unified LLM API, interactive TUI, and terminal coding agent CLI

21.7 Scientific figures

• Ten Simple Rules for Better Figures (Rougier et al. 2014)
• Tufte CSS - style HTML articles like Edward Tufte’s books and handouts, with sidenotes, typography, and tight integration of graphics with text

21.8 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

21.9 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

21.10 Professional advice

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

21.11 Funding

• Building Your Funding Train
• NIH Grant Writing Resources

21.12 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

21.13 Open Science and Reproducibility Initiatives

• The Open Science Manual - an open-source guide from the ARCA group at the University of Padova covering programming good practices, version control, and reproducible workflow tools.
• Openscapes - an open science mentorship and community initiative founded by Dr. Julia Stewart Lowndes, focused on helping research groups transition to data-intensive, reproducible, and collaborative scientific practices through cohort-based Champions programs and shared open tooling.

21.14 Comparable Lab Manuals

Exploring lab manuals from peer research groups helps us identify best practices, adapt proven onboarding workflows, and align our open science standards with the broader computational biology and epidemiology communities:

• Benjamin-Chung Lab Manual (GitHub repository) — The computational epidemiology manual from which our manual originally adapted its structure, covering reproducible R workflows, collaborative development, and computational research practices.
• Fay Lab Manual (GitHub repository) — An Openscapes-origin Quarto manual for quantitative fisheries ecology (UMass Dartmouth), featuring detailed offboarding checklists, departure handoff protocols, and an open science communication philosophy.
• ContextLab Lab Manual (GitHub repository) — The Contextual Dynamics Lab manual at Dartmouth, notable for requiring incoming lab members to make an interactive pull request to learn contribution workflows hands-on.
• Proctor-UCSF DCC Handbook (GitHub repository) — A comprehensive handbook for the Data Coordinating Center at UCSF, focusing on clinical trial data management, REDCap workflows, quality assurance, and public data curation in global health settings.
• Quantitative Marine Ecology Lab Manual (GitHub repository) — A Quarto-based manual for Easton White’s research group at UNH, featuring role-specific administrative checklists and curated reading lists organized by career stage.

21.15 Reading and Watching List

• Good Luck, Have Fun, Don’t Die — A science fiction film directed by Gore Verbinski following a traveler from the future who recruits patrons at a Los Angeles diner to prevent a rogue artificial intelligence from destroying the world.

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/.