e-learning
Visualization of RNA-Seq results with CummeRbund
Abstract
RNA-Seq analysis helps researchers annotate new genes and splice variants, and provides cell- and context-specific quantification of gene expression. RNA-Seq data, however, are complex and require both computer science and mathematical knowledge to be managed and interpreted.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- How are RNA-Seq results stored?
- Why are visualization techniques needed?
- How to select genes for visualizing meaningful results of differential gene expression analysis?
Learning Objectives
- Manage RNA-Seq results
- Extract genes for producing differential gene expression analysis visualizations
- Visualize meaningful information
Licence: Creative Commons Attribution 4.0 International
Keywords: Transcriptomics
Target audience: Students
Resource type: e-learning
Version: 16
Status: Active
Prerequisites:
- Introduction to Galaxy Analyses
- Mapping
- Quality Control
Learning objectives:
- Manage RNA-Seq results
- Extract genes for producing differential gene expression analysis visualizations
- Visualize meaningful information
Date modified: 2023-11-09
Date published: 2017-10-16
Contributors: Andrea Bagnacani, Bérénice Batut, Helena Rasche, Mallory Freeberg, Maria Doyle, Niall Beard, Nicola Soranzo, Saskia Hiltemann
Scientific topics: Transcriptomics
Activity log
