Data & Setup

Workshop Attendees

If you are attending one of our workshops, we will provide a training environment with all of the required software and data. If you want to setup your own computer to run the analysis demonstrated on this course, you can follow the instructions below.

Data

The data used in these materials is provided as a zip file. Download and unzip the folder to your Desktop to follow along with the materials.

Working on your own laptop

If you wish to work on your own laptop during the course and not the training machines you will need to have the latest stable versions of R, RStudio and Bioconductor including the packages listed below.

R and RStudio

This lesson assumes that you have current versions of the following installed on your computer:

The R software itself, and
RStudio Desktop.

R and RStudio require separate downloads and installations. R itself refers to the underlying language and computing environment required to write and read this language. RStudio is a graphical integrated development environment which essentially makes running R much easier and more interactive.

Windows

Download and install all these using default options:

Mac OS

Download and install all these using default options:

R
RStudio

Linux

Go to the R installation folder and look at the instructions for your distribution.
Download the RStudio installer for your distribution and install it using your package manager.

R package installation

In this workshop we make use of open-source software from the R Bioconductor (Huber et al. 2015) project. The Bioconductor initiative provides R software packages dedicated to the processing of high-throughput complex biological data. Packages are open-source, well-documented and benefit from an active community of developers.

Detailed instructions for the installation of Bioconductor packages are documented on the Bioconductor Installation page. The main packages required for this workshop are installed using the code below. Additional packages required for downstream statistics and interpretation are installed as required.

if (!require("BiocManager", quietly = TRUE)) {
  install.packages("BiocManager")
}

BiocManager::install(c("QFeatures",
                       "NormalyzerDE",
                       "limma",
                       "factoextra",
                       "org.Hs.eg.db",
                       "clusterProfiler",
                       "enrichplot",
                       "patchwork",
                       "tidyverse"))

After installation, each package must be loaded before it can be used in the R session. This is achieved via the library function. Here we load all packages included in this course.

library("QFeatures")
library("NormalyzerDE")
library("limma")
library("factoextra")
library("org.Hs.eg.db")
library("clusterProfiler")
library("enrichplot")
library("patchwork")
library("tidyverse")

References

Huber, Wolfgang, Vincent J Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S Carvalho, Hector Corrada Bravo, et al. 2015. “Orchestrating High-Throughput Genomic Analysis with Bioconductor.” Nature Methods 12 (2): 115–21. https://doi.org/10.1038/nmeth.3252.