Data Carpentry R for Genomics

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Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working more effectively with data. The lessons below were designed for those interested in working with Genomics data in R.

Content Contributors: Kate Hertweck, Susan McClatchey, Tracy Teal, Ryan Williams

Lesson Maintainers: Tracy Teal

Lesson status: Under Development

Lessons:

  1. Lesson 00 Before we start
  2. Lesson 01 Introduction to R
  3. Lesson 02 Starting with data
  4. Lesson 03 Introducing data.frame
  5. Lesson 04 Aggregating and analyzing data with dplyr
  6. Lesson 05 Data visualisation with ggplot2

Data

Data files for the lesson are available here:

Requirements

Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to install everything before working through this lesson.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

Twitter: @datacarpentry