Lecture slides on iCloud


In the first half of this lecture we’ll discuss the open-source, cross-platform R/bioconductor software that we will use throughout the course. Then each student will set-up their own laptop to be a powerful, stand-alone bioinformatics workstation.

Learning objectives

  • Brief overview of the tools we’ll use throughout the course (R/Bioconductor, RStudio, etc.)
  • Set-up your laptop with all the software needed for the course

Software everyone will need

I’ll walk you through installing the following software

R Programming Language - The only programming language we’ll work with in class.

RStudio - a development environment for the R programming language.

Sublime text editor - a simple but powerful text editor that is ‘code aware’

Visual Studio Code - an excellent choice for working with virtually any kind of code outside of RStudio. We’ll use this later in the semester for connecting to and working with GitHub repositories.

Additional software Mac users will need

XCode developer tools - Only download if running Mac OS on your laptop.

Additional software Windows users will need

Cygwin - Cygwin will give your system more linux-like capabilities

Git for Windows – This will give you a bash emulator that works really nicely for running standard command-line programs.

Kallisto - This is the software we’ll use for mapping raw reads to a reference transcriptome. Detailed instructions for installing and using Kallisto and other course-related software is available on my lab’s protocols site here.

Lecture video

Part 1 - An overview of the software tools we’ll use on our laptops for the course, as well as options for computing hardware.

Part 2 - Installing software and talking about the relationship between R, RStudio and Bioconductor.