About this site and course

Author
Affiliation

Jelmer Poelstra

Published

August 22, 2025

A photo of a large flock of birds in a foggy fall landscape

Red-winged Blackbirds at Funk Bottoms WA, Wayne Co., Ohio – Jelmer Poelstra

Overview

This is the GitHub website for the course Practical Computing Skills for Omics Data (PLNTPTH 5006), a 3-credit course taught at Ohio State University during the Fall semester of 2025.

The course is taught by Jelmer Poelstra and Menuka Bhandari from the CFAES Bioinformatics Core for the Department of Plant Pathology.


The CFAES logo.

Course description

As datasets have rapidly grown larger in biology, coding has been recognized as an increasingly important skill for biologists. This is especially true in “omics” (genomics, transcriptomics, etc.) research where data can’t typically be analyzed on a desktop computer where cutting-edge software has a command-line interface, and where workflows include many steps that need to be coordinated.

In this course, students will gain hands-on experience with a set of general and versatile tools for data-intensive research in omics and beyond. The course will focus on foundational skills such as working in the Unix shell and writing shell scripts, managing software and submitting jobs at a compute cluster (the Ohio Supercomputer Center), and building flexible, automated workflows. Additionally, the course will cover reproducibly organizing, documenting, and version-controlling research projects. Taken together, this course will allow students to reproduce their own research, and enable others to reproduce their research, with as little as a single command.

Main topics taught

  • Reproducibility: project documentation with Markdown, file organization, data and management and sharing
  • Unix shell: basics, scripting, running command-line programs
  • Supercomputer (OSC) usage: basics, software, and running Slurm batch jobs
  • Version control with Git and GitHub
  • Automated pipelines with Nextflow and nf-core
  • R: Basics, data wrangling & visualization, Quarto, and specifics to omics data
  • Omics data analysis basics, with a focus on high-throughput sequencing data

CarmenCanvas website

If you are a student in this course, you should also refer to its CarmenCanvas site.

O’Neil (2019)

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References

O’Neil, Shawn T. 2019. A Primer for Computational Biology. Oregon State University. https://open.oregonstate.education/computationalbiology/.