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Coursera

Researcher's guide to RNA sequencing data

Fred Hutchinson Cancer Center via Coursera

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Overview

Class Central Tips
This course is a follow up course to "Choosing genomics tools" which dives into further detail about RNA informatics methods! This course is for individuals who: - Have taken Researcher's Guide to Fundamentals of Omic Data - Have RNA data and don’t know what to do with it. - Want a basic overview of their RNA focused data type. - Want to find resources for processing and interpreting RNA data What this course will cover: - Fundamentals of RNA methods. - Resources you may consider looking into for your own purposes. - Questions you should ask yourself and your colleagues about your goals and experimental design. What this course will NOT cover: - Code needed to process your data. - Details about every type of experimental design. - Everything you’d need to know to make you a computational biologist. In other words we still highly encourage you to consult your informatics and computational colleagues, especially those who may have done any handling of data you are trying to learn about.

Syllabus

  • Introduction
    • In this first module we introduce the goals of this course an do an overview of the available methods for RNA methods, otherwise known as gene expression.
  • Bulk RNA-seq
    • In this module we dive into Bulk RNA-seq methods for evaluating gene expression of tissue.
  • Single Cell RNA-seq
    • In this module we dive into single cell RNA-seq methods for evaluating gene expression of single cells.
  • Spatial Transcriptomics
    • In this module we dive into gene expression of tissue but with spatial information.
  • Wrapping Up
    • To wrap up this course, we have a quick section about gene expression microarrays before we wrap up the course with a final course knowledge check.

Taught by

Candace Savonen, MS

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