ECE365: R for Jupyter

In the Biological Data Analysis part of this course, we will be making use of R statistical programming language and its packages developed for machine learning, big data, and specialized analysis for biological data. Assignments will be be distributed as Jupyter Notebooks which will need to be modified and turned in.

Depending on the method, installation of R, its Jupyter kernel, and the basic packages required for this part of the course will take a while. Please start early and be patient. Be sure that you are able to run the package installations and plotting commands in the first lab as soon as possible so there is time to troubleshoot any installation issues.

Using Anaconda to Install R for Jupyter

If you already used Continuum Anaconda to install and set up your Python3 Jupyter for the previous parts of the class, here are a few resources for installing the components for running notebooks with the R kernel.

Installation with Anaconda Navigator, here
Installation with Anaconda Prompt, here

Alternative Installation Options

Other options for installation without Anaconda explicitly are available.

Installation with homebrew, here
Jupyter Notebook for Data Science Docker image, here

Installing Packages from CRAN and Bioconductor

The final section of the first assignment covers how to install packages from within a Jupyter Notebook. Please make sure you can complete this section of the assignment as soon as possible to identify possible issues with your Jupyter configuration.

R and Bioconductor Resources

Finally, a few web resources that might provide guidance if you need additional documentation or help: