Summary and Schedule

Callout

Pomona College HPC Workshop Series

This workshop is part of the Pomona College Research Computing Workshop Series, adapted from Programming with R by Software Carpentry.

Cluster: sagehen.hpc.pomona.edu Web Portal: OnDemand Support:

R is available on the Sagehen HPC cluster via module load r (module names are lowercase). You can also use RStudio Server through the OnDemand web portal for interactive work.

Adapted for Pomona College by Andrew Wilson, ITS Research Computing. Licensed under CC-BY 4.0.

The best way to learn how to program is to do something useful, so this introduction to R is built around a common scientific task: data analysis.

Our real goal isn’t to teach you R, but to teach you the basic concepts that all programming depends on. We use R in our lessons because:

  1. we have to use something for examples;
  2. it’s free, well-documented, and runs almost everywhere;
  3. it has a large (and growing) user base among scientists; and
  4. it has a large library of external packages available for performing diverse tasks.

But the two most important things are to use whatever language your colleagues are using, so you can share your work with them easily, and to use that language well.

We are studying inflammation in patients who have been given a new treatment for arthritis, and need to analyze the first dozen data sets of their daily inflammation. The data sets are stored in CSV format (comma-separated values): each row holds information for a single patient, and the columns represent successive days. The first few rows of our first file look like this:

0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0
0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1
0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1
0,0,2,0,4,2,2,1,6,7,10,7,9,13,8,8,15,10,10,7,17,4,4,7,6,15,6,4,9,11,3,5,6,3,3,4,2,3,2,1
0,1,1,3,3,1,3,5,2,4,4,7,6,5,3,10,8,10,6,17,9,14,9,7,13,9,12,6,7,7,9,6,3,2,2,4,2,0,1,1

We want to:

  • load that data into memory,
  • calculate the average inflammation per day across all patients, and
  • plot the result.

To do all that, we’ll have to learn a little bit about programming.

Prerequisite

Prerequisites

Learners need to understand the concepts of files and directories (including the working directory). We often use RStudio to teach this lesson, but it is not required.

Acknowledgments

Developed by Andrew Wilson, Director of Research Computing and Digital Scholarship at Pomona College, with Andrei Motchenko, who tested, edited and produced screenshots for the workshop series.

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

If you have a Pomona College HPC account, you can complete this workshop entirely in the browser via the Sagehen OnDemand portal — no local installation required:

  1. Sign in at https://ondemand.hpc.pomona.edu with your Pomona credentials and DUO MFA at https://duo.pomona.edu.
  2. Open the Interactive Apps > RStudio Server app and request a small session on the amd partition (e.g., 4 cores, 16 GB RAM, 4 hours).
  3. Save your project to /bigdata/lab/<labname>/your-username/ so it persists between sessions and is backed up alongside your data.

If you do not yet have an HPC account, contact its-hpc@pomona.edu to request one.

This lesson assumes you have current versions of the following installed on your computer (or available in your OnDemand RStudio session on Sagehen):

  1. the R software itself, and
  2. RStudio Desktop.

You also need to download some files to follow this lesson:

  1. Make a new folder in your Desktop called r-novice-inflammation.
  2. Download r-novice-inflammation-data.zip and move the file to this folder.
  3. If it’s not unzipped yet, double-click on it to unzip it. You should end up with a new folder called data.
  4. You can access this folder from the Unix shell with:

BASH 

$ cd
$ cd Desktop/r-novice-inflammation/data