yfwang27 / rnaseq_short

RNAseq (short course)

##The Course

This course introduces some of the fundamental concepts and tools of RNA-seq analysis in R/Bioconductor. This course is a shortened version of our full course

Each section is presented as both HTMl and Rpres markdown ( to allow for intergration of the presentation in the RStudio enviroment itself). Exercises and answer sheets are included after all subsections to practice techniques and provide future reference examples.

Course material and exercises are available to view as rendered HTML slides or single page HTML at http://mrccsc.github.io/RNAseq_short/.
All material is available to download under GPL v3 license.

For information on other courses run by our team see our github IO page.

The Team

This course was created and conducted by the MRC Clinical Sciences Centre Bioinformatics Team at Imperial College London, Hammersmith Hospital.
For more information on the team see our github IO page.

This course is free for MRC CSC and Imperial staff and students. If you would like to attend a future course contact [email protected].

Setting up.

Install R.

R can be installed from the R-project website.
R 3.1.0 or higher is required for this course.

http://www.r-project.org/

Install RStudio.

RStudio can be installed from the R-project website.

http://www.rstudio.com/

Install required packages.

Having downloaded R and RStudio, some additional packages are required (rmarkdown and ggplot2).
To install these,

• First launch RStudio
• Install the packages in the R console

source("https://bioconductor.org/biocLite.R")
biocLite("DESeq2")
biocLite("goseq")
biocLite("RColorBrewer")
biocLite("ggplot2")
biocLite("pheatmap")
biocLite("KEGG.db")
biocLite("org.Mm.eg.db")
biocLite("biomaRt")

Download the material

The material can either be downloaded as a zip

wget https://github.com/mrccsc/RNAseq_short/archive/master.zip ./

or checked out from our Github repository https://github.com/mrccsc/RNAseq_short/