Course Description

The goal of this course is to provide students with an overview of tools, methods, and concepts used in the broad sphere of computational genomics.  Although we will use tools occasionally, the primary focus of materials will guide students to learn about available computational strategies and how, why, and when to use them.  Whenever students are asked to use tools, they will be point-and-click applications that do not require coding.  After taking this course and learning about the breadth of topics under the umbrella of computational genomics, students will be well-equipped to decide which more advanced topics to study to deepen their knowledge and learn relevant skills.  Specific topics covered will include genome-wide association studies (GWAS), variant detection, next-generation sequencing including single-cell RNAseq, comparative genomics, and cross-species evolution-based analyses.

Learner Outcomes

When you complete the course successfully, you will be able to:

  • Describe the experiments that produce data for computational genomics analyses
  • Interpret the results of computational genomics analyses
  • Evaluate the relevancy of computational tools to perform genomics analyses
  • Appreciate the breadth of topics in computational genomics and feel empowered to gain deeper understanding of their specific area(s) of interest


This course applies toward the Bioinformatics Endeavor digital badge.

Textbook Information

There is no textbook for purchase required for this course.


There are no prerequisites for this course.

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