Summary and Schedule

Callout

Pomona College HPC Workshop Series

This workshop is part of the Pomona College Research Computing Workshop Series, adapted from R for Reproducible Scientific Analysis by Software Carpentry.

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

R and RStudio are available on Sagehen HPC via module load r or through the OnDemand portal. Reproducible analysis practices are essential for HPC research workflows.

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

an introduction to R for non-programmers using gapminder data

The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis.

The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop.

A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.

Prerequisite

Prerequisites

Understand that computers store data and instructions (programs, scripts etc.) in files. Files are organised in directories (folders). Know how to access files not in the working directory by specifying the path.

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.

R for Reproducible Scientific Analysis - Setup Guide

This workshop teaches you how to use R and RStudio for reproducible data analysis, focusing on the Gapminder dataset. You have two setup options: use R on Pomona’s Sagehen HPC cluster, or install R locally on your computer.

Using R on Sagehen is ideal for this workshop because: - Pre-installed software (no installation needed) - Shared Gapminder data files available - Easy access via web browser - Collaborative environment

Access R on Sagehen via OnDemand

Step 1: Log into OnDemand

  1. Open browser: https://ondemand.hpc.pomona.edu/
  2. Log in with Pomona credentials (Duo authentication required)
  3. Click “Interactive Apps” in the top menu
  4. Select “RStudio Server” (or “RStudio” if available)

Step 2: Request RStudio Session

When prompted, enter: - Number of hours: 2-4 (for workshop) - Memory: 8 GB (minimum) - CPU cores: 2-4 - Click “Launch”

Wait 30-60 seconds for the RStudio window to appear.

Step 3: Verify RStudio Works

In the RStudio console, type:

R 

# Check R version
R.version
# Should show R version 4.x or later

# Check RStudio
rstudioapi::getVersion()
# Should show RStudio version

You’re ready for the workshop!

Ending Your Session

After the workshop: 1. Click “Home” (top-left) 2. Under “My Interactive Sessions”, click “Delete” 3. Your session closes and compute time stops

Option 2: Local Installation (If You Prefer)

If you prefer R on your personal computer instead of Sagehen HPC:

Install R

Download and install the latest version of R from https://www.r-project.org/:

  • Windows: Click “Download R for Windows” → “base” → Download the installer
  • Mac: Click “Download R for (Mac)” → Choose your processor type (Intel or Apple Silicon)
  • Linux: Follow distro-specific instructions or use package manager:
    • Ubuntu: sudo apt install r-base
    • Fedora: sudo dnf install R

Install RStudio

Download RStudio Desktop (free version) for your operating system.

RStudio is an IDE that makes R much easier to use.

Test Your Installation

After installing R and RStudio:

  1. Open RStudio
  2. In the console (lower-left), type:

R 

R.version
# Should show R 4.x or later

Workshop Setup Verification

For Sagehen HPC Users

Verify you have access to workshop materials:

R 

# Check workshop materials location
list.files("/data/gapminder/")
# Should show: gapminder.txt, continents.csv, or similar

# Check what files are available
dir("/data/gapminder/")

If files exist, you can use Sagehen for the workshop. If not, contact .

For Local R Installation

You don’t need pre-existing files; you’ll download Gapminder data during the workshop.

Loading Modules on Sagehen HPC

If using Sagehen via terminal (not OnDemand RStudio), load R modules:

BASH 

# SSH into Sagehen
ssh <myusername>@sagehen.hpc.pomona.edu

# Check available R versions
module avail R
# Shows: r/4.2.2, r/4.2.3, r/4.4.1, r/4.5.1 (D)

# Load R (module names are lowercase)
module load r/4.5.1  # (or just `module load r` for the default)

# Start R
R

# In R console
> R.version
# Verifies it works

Installing Packages on Sagehen HPC

For Sagehen users, install workshop packages in user space:

R 

# In R console (started via `module load r`)

# Set user library path
dir.create(Sys.getenv("HOME"), ".R/library", recursive = TRUE)
.libPaths(file.path(Sys.getenv("HOME"), ".R/library"))

# Install ggplot2 (for visualization)
install.packages("ggplot2", repos = "http://cran.r-project.org")
# Answer 'yes' to "Create a personal library in..." if prompted

# Install tidyverse (collection of useful packages)
install.packages("tidyverse", repos = "http://cran.r-project.org")

# Verify installation
library(ggplot2)
library(dplyr)
# Should load without errors

Downloading Gapminder Data

Via Sagehen HPC (OnDemand RStudio)

The Gapminder data is already available at:

R 

# Read Gapminder data
gapminder <- read.csv("/data/gapminder/gapminder.csv")

# View first few rows
head(gapminder)

# Check dimensions
dim(gapminder)
# Should show: 1704 rows x 6 columns

If the file path doesn’t work, download it from:

R 

# Download from official source
url <- "https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/data/gapminder_data.csv"
gapminder <- read.csv(url)

Via Local R Installation

Download the Gapminder data file:

R 

# In RStudio console
url <- "https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/data/gapminder_data.csv"
download.file(url, "gapminder_data.csv")

# Read it into R
gapminder <- read.csv("gapminder_data.csv")

# Verify
head(gapminder)
dim(gapminder)

Alternatively, download the CSV directly and open in RStudio.

RStudio Configuration

Default Settings (Usually Fine)

RStudio works well with default settings. Optional improvements:

Tools → Global Options: - General: Uncheck “Save workspace to .RData” - Code → Editing: Enable “Soft-wrap R source files” (easier reading) - Appearance: Choose your preferred theme (light/dark) - Pane Layout: Default layout works; customize if preferred

Setting Working Directory

In RStudio, set where your data files are:

R 

# Check current working directory
getwd()

# Set to your data folder
setwd("~/data/")  # or your actual path

# Verify
list.files()
# Should show your data files

Troubleshooting

“Packages won’t install on Sagehen HPC”

If you get permission errors:

  1. Create user library directory:

R 

dir.create(file.path(Sys.getenv("HOME"), ".R"), showWarnings = FALSE)
dir.create(file.path(Sys.getenv("HOME"), ".R/library"), showWarnings = FALSE)
  1. Set library path before installing:

R 

.libPaths(file.path(Sys.getenv("HOME"), ".R/library"))
install.packages("ggplot2")

“Can’t find Gapminder data”

  • Check file path: list.files("/data/gapminder/") or list.files(".")
  • Download from GitHub (command shown above)
  • Contact if /data/gapminder not available

“RStudio won’t start on OnDemand”

  • Check internet connection
  • Try refreshing the page
  • Check available compute resources (may need to wait)
  • Contact

“R version is too old”

Sagehen may have multiple R versions. Request newer one:

BASH 

module avail r
# See available versions: r/4.2.2, r/4.2.3, r/4.4.1, r/4.5.1 (D)
module load r/4.5.1  # Load desired version

Before the Workshop

Verify your setup is working:

For Sagehen users: - [ ] Can log into OnDemand (https://ondemand.hpc.pomona.edu) - [ ] Can launch RStudio from Interactive Apps - [ ] Can type R.version in console and see R 4.x - [ ] Can see /data/gapminder/ data files (or download them) - [ ] Can load ggplot2 package

For local R users: - [ ] R installed from https://www.r-project.org/ - [ ] RStudio Desktop installed - [ ] Can open RStudio and see R console - [ ] Can download Gapminder CSV file - [ ] Can read CSV with read.csv("gapminder_data.csv")

Getting Help

  • Sagehen issues: Email
  • R/RStudio questions: Office hours (see workshop info)
  • Data questions: Ask instructor during workshop
  • Debugging: Use ?function_name in R to see help

Next Steps

Once setup is complete, you’re ready to start the workshop!

Episode 1: Introduction to R and RStudio walks through the basics and uses Gapminder data to teach fundamental R concepts.

Let’s learn reproducible data analysis!