There are numerous algorithms available as freeware or by public access in the cloud that make complex biological sequence analyses accessible to everyone. This self-paced, introductory course, aimed at professionals who want to break into the sequencing-related field of bioinformatics, explores important public access tools used for analyzing biological sequence data.

Through hands-on examples and exercises, you will learn how to access public databases for raw sequence data and perform the basic steps in processing next-generation sequence data for RNA, DNA, and ChIP sequencing data to obtain interpretable results.

You will get to explore the analytical parts of next-gen sequencing without having to do wet lab work because we’ve designed this course for people who are interested in a quick introduction to tools that allow for quick problem-solving without a deep theoretical understanding of how the tools work.

Learning Outcomes

At the conclusion of the course, you should be able to

• Process raw sequence for DNA and RNA for use in analytical algorithms
• Use Galaxy and R programs for performing data analyses
• Generate graphical outputs from the analytical results
• Annotate analytical results to convey biological meaning about the samples analyzed

Topics Include

• Public access tools used for analyzing biological sequence data

Working knowledge of:

• Communication and collaboration tools such as Google Workspace, Microsoft Office, or LibreOffice
• Learning Management Systems (LMS) such as Canvas including navigation links, modules, etc.
• The concepts of molecular and cellular biology.

Additional Information

Please review section notes to view the full schedule.

Most job postings for technicians and scientists in the molecular biology field ask for experience with next-gen sequencing. Having experience with the analytical tools is considered a plus on job applications.