The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
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Researcher's guide to omic fundamentals
This course is part of Researcher's Guide to Omic Data Specialization
Recommended experience
What you'll learn
By the end of the course you will confidently be able to use tutorials and resources to understand and interpret your genomic data.
Details to know
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May 2024
15 assignments
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There are 5 modules in this course
In this module, we cover the basics of what will be covered in this course and what you should expect. Next we get into an overview of what omic data types and their workflows often look like.
What's included
3 videos3 readings2 assignments1 discussion prompt
In this module, we cover some considerations for how to choose between different omics tools. Then we talk about what is metadata and how do you make sure you get the most of your metadata?
What's included
2 videos2 readings4 assignments2 discussion prompts
In this module, we build on the previous module's generalities about omic data and get into specifics about sequencing data and microarray data.
What's included
2 videos2 readings4 assignments
In this module, we discuss what are general data analysis tools you may want to consider using. Lastly we cover some basics about annotation that are involved in every omic data analysis workflow.
What's included
1 video3 readings4 assignments
Now that you've learned some fundamentals about omic data, in this section we have a final quiz that tests your absorption of what we've discussed. We also have a Tool Glossary of recommended tools you may want to consider using for your next steps with your omic data.
What's included
1 video2 readings1 assignment
Instructor
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Recommended if you're interested in Data Analysis
Fred Hutchinson Cancer Center
Fred Hutchinson Cancer Center
Coursera Project Network
Fred Hutchinson Cancer Center
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