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Writer's pictureHeidi Waite

Learning R: Resources

Updated: May 20, 2020


Programming - that's just for computer geeks, right? Nope, biologists also program...and a lot actually! Biologists use a programming language called R to explore their data, create cool figures, and analyse their data. Programming is a scary word, but I'm here to tell you it's not impossible. If I can learn, you can too!


In this blog post, I'll share some of the resources that I used to start learning R and other resources I currently use to keep learning.


1. Getting to know R and Rstudio*

*R is the programming language, RStudio is an Integrated Development Environment (IDE) and the interface you'll mainly use (but still requires R to be downloaded)



I'd suggest you start by first learning the basics of how the programming language functions and what the interface looks like. For that, I used Datacamp. Datacamp has some great introductory videos and exercises. Here is also a youtube video playlist with useful introductory videos. [They also have a lot of other cool videos once you are more advanced on Tidyr, data science in R.]



2. Start Dealing with Data

I used two textbooks, R Cookbook and A Beginner’s Guide to R, to start messing around with data. They also have some sections on getting started with R and R basics.


Some other useful youtube videos.


3. Learn tidyverse

Tidyr is a package in R that helps you make your data "tidy" - it helps you get your data in order. This makes it easier to create fun graphs and analyse data. I'm still learning tidyr, but it's a game changer! I'm using a book called R for Data Science. It assumes you have at least some basic knowledge of R programming. I also highly recommend you do the exercises in each chapter. There is also a solutions manual to check your answers.


4. Using R for Visualisation

I've put together a few resources for data visualisation. Get ready to make some beautiful graphs and figures!



Most other books in the other sections above also have chapters on data visualization.


5. Using R for Statistical Analysis

Here I've also put some resources for learning to do stats in R.



6. Other Resources

Datacamp - lots of good videos

When in doubt: YouTube it, search it on google, or look through the online forum called Stack Overflow

Regression Modeling Strategies - free book download



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And to get more practice in R, try participating in Tidy Tuesday. Every Tuesday, this forum shares a public dataset. Users then use their tidyr skills to make amazing figures and they share them on Twitter. It's a great way to practice all the skills you've gained.


I hope this was useful and I wish you luck!

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