Resources

This page contains (mostly) third-party resources you can use to learn computing for data science and bioinformatics, focusing on open source and reproducible approaches. These resources include online short courses, workshops, blog posts, and books (some $$) that I’ve found over the years which seem useful for others.

Do you have or know of a resource you think I should include? Let me know with an issue here!

Comprehensive resources

Introduction to Data Science course (2023) by Rafael Irizarry
- A full college-level semester course in data science with R, git, and Quarto
Materials to learn bioinformatics at home, compiled by Harvard Informatics
- Links out to various UNIX, R, Python, statistics, git(hub), and miscellaneous omics resources
Practical Computing for Biologists, by Steve Haddock and Casey Dunn
- A beginner-level introduction to UNIX, regular expressions, Python, and general skills in computing
Bioinformatics Data Skills, by Vince Buffalo
- An intermediate-level resource on UNIX skills for bioinformatics, reproducible, project management, R, and “big data” genomics analyses
Software Carpentry and Data Carpentry
- Free lessons and curricula for learning computing and data management skills

Learn UNIX (command line)

Learn R and tidyverse

Big Book of R compiled by Oscar Baruffa
Learning-R-Resources compiled by Joscelin Rocha Hidalgo
The {introverse} and linked resources within by Stephanie J. Spielman
R for Data Science by Hadley Wickham
Advanced R by Hadley Wickham
Mastering Shiny by Hadley Wickham
Engineering Production-Grade Shiny Apps by Colin Fay, Sébastien Rochette, Vincent Guyader and Cervan Girard

Learn Data Visualization

Data Visualization: A Practical Introduction by Kieran Healey
ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen.
Fundamentals of Data Visualization by Claus Wilke

Resources

Comprehensive resources

Learn UNIX (command line)

Learn R and tidyverse

Learn Data Visualization

Learn Markup Languages