e-learning
Downstream Single-cell RNA analysis with RaceID
Abstract
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
- What is normalisation and why is it necessary?
- How many types of unwanted variation are there?
- How are biological phenotypes clustered?
- What is the difference between PCA and tSNE?
- What is the difference between cell trajectory and cell fate?
Learning Objectives
- Filtering, normalising, and clustering cells in a matrix
- Assessing the quality of individual clusters
- Inferring cell type lineages
- Examining gene expression
- Determining the top most expressive genes per cluster
- Correcting for unwanted variation
Licence: Creative Commons Attribution 4.0 International
Keywords: Single Cell, work-in-progress
Competency level: • Beginner
Target audience: Students
Resource type: e-learning
Version: 7
Status: Draft
Prerequisites:
- Introduction to Galaxy Analyses
- Single-cell quality control with scater
Learning objectives:
- Filtering, normalising, and clustering cells in a matrix
- Assessing the quality of individual clusters
- Inferring cell type lineages
- Examining gene expression
- Determining the top most expressive genes per cluster
- Correcting for unwanted variation
Date modified: 2025-02-14
Date published: 2019-03-25
Authors: Mehmet Tekman, 
Alex Ostrovsky
Contributors: Mehmet Tekman, Simon Bray, Anthony Bretaudeau, Björn Grüning, Bérénice Batut, Helena Rasche, Pavankumar Videm, Saskia Hiltemann, Stéphanie Robin
Scientific topics: Transcriptomics
External resources:
Activity log
