Workshops and courses
Learning Pathway Introduction to Galaxy and Single Cell RNA Sequence analysis
Date: No date given
This learning path aims to teach you the basics of Galaxy and analysis of Single Cell RNA-seq data.
You will learn how to use Galaxy for analysis, and an important Galaxy feature for iterative single cell analysis. You'll tbe guided through the general theory of single analysis and then perform a basic analysis of 10X chromium data. For support throughout these tutorials, join our Galaxy single cell chat group on Matrix to ask questions!
Keywords: beginner, single-cell
Learning objectives:
- Be familiarised with the main types of clustering techniques and when to use them.
- Construct and run a cell type annotation for the clusters
- Construct and run a dimensionality reduction using Principal Component Analysis
- Demultiplex single-cell FASTQ data from 10X Genomics
- Describe an AnnData object to store single-cell data
- Evaluate quality of single-cell data and apply steps to select and filter cells and genes based on QC
- Execute data normalization and scaling
- Explain the preprocessing steps for single-cell data
- Grasp what dimension reduction is, and how it might be performed.
- Identify highly variable genes
- Identify marker genes for the clusters
- Know the types of variation in an analysis and how to control for them.
- Learn about transparent matrix formats
- Learn how they are propagated
- Learn how to extract and run a workflow
- Learn how to set name tags
- Learn how to share a history
- Learn how to upload a file
- Learn how to use a tool
- Learn how to view histories
- Learn how to view results
- Perform a graph-based clustering for cells
- To understand the pitfalls in scRNA-seq sequencing and amplification, and how they are overcome.
- Understand the importance of high and low quality cells
Event types:
- Workshops and courses
Sponsors: Australian BioCommons, ELIXIR Europe, University of Freiburg
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