This companion textbook supports my Spring 2026 course "BIOL 5860/6860: Bioinformatics and Genome Analysis". It provides a hands-on survey of computational approaches to “reading” biological data. As biologists with genetics and computational biology prerequisites, students will already know how to frame biological questions and wrangle basic code. This course builds directly on that foundation to demystify the “black box” of bioinformatics tools, showing them how to move from raw sequencing data to biological insight.
This book was developed in R using the package Quarto. It is written in markdown and rendered to HTML. The code and writing has been largely assisted by AI.
The field of Bioinformatics moves fast — back when I was in graduate school, I first learned 454 sequencing and applied it to my PhD work, and it is now long obsolete. Based on this lived experience, my goal in teaching bioinformatics is to avoid teaching specific tools that may change by the time students graduate. Instead, this book emphasizes adaptability: the core concepts, file formats, quality control practices, and workflow thinking that transfer across platforms and projects. It includes a Lab Manual with 10 hands-on labs that progress from exploratory (“find a genome paper on your favorite organism”) to practical (GATK variant calling on HPC) to independent (semester-long group research projects where you discover and master new tools yourselves).
I am making this resource public with the goal that other educators can use and adopt this for their own courses. The use of a custom-online textbook avoids costly fees for students, increasing accessibility of students from any background, and removes the dependence of faculty on LMS platforms such as Canvas. If you find anything factually incorrect or out of date, please let me know. My goal is to make updates each time I teach my Bioinformatics course and publish updated versions.
Whether you are a fellow teacher or a student, I hope you find this resource useful! Thanks for your interest.
Citation: Laurie Stevison. (2026). StevisonLab/Bioinformatics: First Edition (v1.0). Zenodo. https://doi.org/10.5281/zenodo.20218119.
