methylation_EWAS_workshop

This is a basic EWAS tutorial, introducing concepts for analysing methylation data.

There is a webpage version of the tutorial located here. You can load this and follow along as you run through this on your computer, if you wish to copy paste code please feel free to do so.

Data

The workshop uses public Illumina 450K data from several studies (GSE40279, GSE48472, GSE41114, GSE42700, GSE46573, GSE48472, GSE50586). It is currently designed to investigate the methylation differences between blood (whole blood) and buccal (cheek swabs) tissues. It is aimed at giving a very basic overview of the structure and type of data used in EWAS as well as a few of the available tools and methods to explore this data.

Required software and packages

You will need to ensure you have the following installed on your system:

the latest version of R: https://cran.r-project.org/
RStudio (optional but recommended): https://www.rstudio.com/products/rstudio/download2/
the R package minfi: https://www.bioconductor.org/packages/release/bioc/html/minfi.html
- to install minfi run the following within R/RStudio:
  - source("https://bioconductor.org/biocLite.R")
  - biocLite("minfi")
the R package FactoMineR
- install.packages('FactoMineR')

NOTE: this workshop should work across all OS (Windows, Linux, Mac) as long as the above are correctly installed.

Set up

1. obtain the workshop files

Once the above software and R packages are installed set up is as simple as downloading or cloning this repository, it contains all the data and scripts required for the workshop.

Download

You can download this repository as a zip file (see top of this page for Download button) and extract to the folder methylation_EWAS_workshop where appropriate on your system.

Clone

If you are familiar with git and GitHub you can clone into this repository:

git clone https://github.com/sirselim/methylation_EWAS_workshop.git

2. move to the correct directory and start working

Open R/RStudio and ensure that your working directory is set to the methylation_EWAS_workshop directory, then open the EWAS_analysis.R script and follow along.