This deploys a Binder that exposes the RStudio UI instead of a Jupyter Notebook. It also installs several packages from the tidyverse, and includes a demo script to show off functionality. Plus, I added my favorite R-related items for bioinformatics.

To start your RStudio session once the Binder server has launched and you are greeted with the Jupyter dashboard, click on "New" in the top right, and at the bottom will be RStudio Session. Click that and your RStudio session will begin momentarily!

See instructions.ipynb for more details.

I had found I could do all or some of the following once running when launched from example Binder in the running RStudio session:

source("https://bioconductor.org/biocLite.R")
biocLite(c("tximport","DESeq2","readr","RColorBrewer","pheatmap")) #for tximport and DESeq2 
install.packages('rjson') #for tximport and DESeq2 
biocLite(c("edgeR","DOSE","KEGGREST","pathview","clusterProfiler")) # for EdgeR
OPTIONAL: biocLite(c("tximportData"))  #for tximport and DESeq2 

But those take a long time to install that way. I had tried adding using biocLite() approach in a Dockerfile first based on here, which was part of past of the image the Binder example was using. However, I couldn't get the libraries I had added to work because of errors about version of R and bioconductor packages not being compatible. Luckily when looking into something else, I saw here that taylorreiter was using RNA-seq and the approach there was to use the install.r (comparable to install.R I noted was already set up in the Dockerfile for example Binder in the running RStudio session to handle the biocLite() installations). Moving the handling of the Bioconductor-controlled packages there, seemed to fix my issues. As described here the biocLite() approach is the recommended way because it overcomes issues the 'standard' way R packages are installed.

Whet set up January 2018, it was getting the versions of items associated with Bioconductor 3.6 (R version 3.4.2). See here for help about checking version in running RStudio session or getting versions of Bioconductor packages if you know what version of Bioconductor you had used or are using.