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.

Skills Needed

• To be successful in this class all students should have working knowledge of Google’s G Suite or Microsoft Office, proper email etiquette, and essential understanding of Canvas.
• A working knowledge of the concepts of molecular and cellular biology.

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

Notes

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.