BioMonth - CSC supercomputing and data management for bioscientists

RStudio is a graphical interface to the software R and is heavily used in statistical data analysis. Main advantages of using Rstudio as a docker container include:

Reproducibility of analysis results
Collaboration with colleagues

Learning Objectives:

Launching RStudio as a docker container
Performing a simple data analysis task using R

How to run (recap from earlier tutorial)

Run rstudio with default password as below:

docker run -d -p 8080:8787 -i -t rocker/rstudio

Launch rstudio with new password as below:

docker run -d -p 8080:8787 -e USERPASS=secretpassword  -i -t rocker/rstudio

How to access rstudio server

To access the app, point your web browser at http://localhost:8080/

Perform PCA analysis

Principal component analysis (PCA) is a method of extracting important variables (in form of components) from a large set of variables available in a data set. It extracts low dimensional set of features from a high dimensional data set with a motive to capture as much information as possible.

we will use prcomp function from stats package.

data(iris)
log.ir <- log(iris[, 1:4])

ir.pca <- prcomp(log.ir,
                 center = TRUE,
                 scale. = TRUE) 
# plot method
plot(ir.pca, type = "l")

Install an R package called “ggplot2” in rstudio

More often we need to install some R packages in rstudio to perform our analysis. Let’s try to install ggplot2 package here as an example.

# On Rstudio GUI use the following command
install.packages("ggplot2", type = "source")
or 
# commandline approach
docker exec -it <CID> bash 
R -e  'install.packages("ggplot2", type = "source")'

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