YoVDO

Researcher's guide to omic fundamentals

Offered By: Fred Hutchinson Cancer Center via Coursera

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Course Description

Overview

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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. This course is written for individuals who: - Have genomic data and don’t know what to do with it. - Want a basic overview of genomic data types. - Want to find resources for processing and interpreting genomics data. Goal of this course: Equip learners with tutorials and resources so they can understand and interpret their genomic data in a way that helps them meet their goals and handle the data properly. This includes helping learners formulate questions they will need to ask others about their data What is not the goal Teach learners about choosing parameters or about the ins and outs of every genomic tool they might be interested in. This course is meant to connect people to other resources that will help them with the specifics of their genomic data and help learners have more efficient and fruitful discussions about their data with bioinformatic experts. The course is intended for students in the biomedical sciences 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.

Syllabus

  • Introduction
    • 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.
  • Considerations for omic projects
    • 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?
  • Omic Basics
    • In this module, we build on the previous module's generalities about omic data and get into specifics about sequencing data and microarray data.
  • Annotation and general tools
    • 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.
  • Wrapping Up
    • 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.

Taught by

Candace Savonen, MS

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