Course Description

In this course, students will learn to analyze data generated by a variety of sequencing techniques (such as DNAseq, RNAseq and CHIP-seq) particularly in relation to biomedical applications (such as analysis of gene expression and identification of medically relevant sequence variation). While recorded lectures and readings will provide necessary background, the course emphasizes hands-on, self-paced lessons featuring real-world data sets to give the learner experience with all major steps of sequencing analyses, from filtering of raw data to creating polished figures. As the course progresses, students will work on a term project in which they design a sequencing project based on their own research interests. To make this course accessible to all students, we will focus on the use of publicly available resources, such as the NCBI SRA and the Galaxy platform, that can be accessed from anywhere.

Learner Outcomes

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

  • Compare and contrast a variety of modern sequencing techniques and their applications.
  • Utilize and compare several platforms for the analysis of sequencing data.
  • Carry out bioinformatics analyses on biomedically relevant sequencing data sets.
  • Interpret the results of these analyses by generating figures and written summaries.
  • Develop a sequencing and analysis plan for a project relevant to their own research interests.


This course applies toward the Bioinformatics Endeavor digital badge.

What FAES Learners are Saying

“I thought the hands-on learning was extremely useful and intuitive, even when the concepts were intimidating. I think if this class were more lecture based I would have had much more trouble, but the hands-on tutorials made jumping into the analysis easy. I didn't really have a chance to overthink it.” - Jennifer G.

Textbook Information

There is no textbook for purchase required for this course.


This course has no official pre-requisites. However, the course material assumes that you are familiar with general genetics and statistics concepts at the level expected from undergraduate coursework. No prior knowledge of bioinformatics data analysis or programming languages is required.

Additional Information

This course is for learners who have experience in genetics and biology, and want to deepen their knowledge of the process required for analyzing sequencing data. 

Follow the link to review FAES Tuition Refund Policy.

Funding Justification Guide

Some labs and institutes may have specific funds set aside for trainees to continue their education and professional development. FAES has created a guide intended to help trainees request funds that may be available and, if they are available, request use of the training funds for continued professional development. More details

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