Single-Cell RNA-Seq Analysis Using Galaxy
This hands-on workshop will cover the basics of single-cell RNA-Seq analysis, using the Galaxy platform. Starting from a table of gene counts we will evaluate, filter, annotate and visualise the data. We will also cover clustering, cell type identification and differential expression.
Galaxy Australia is a platform that provides a simple and user-friendly interface to bioinformatics tools. The output we will generate is suitable for further analysis within Galaxy Australia, or locally.
Recommended Participants
Life scientists planning or running single cell RNAseq experiments (or mining public data), who want to perform their own analyses. All analysis is performed via the web browser.
Participants should have a basic understanding of single cell RNAseq technology. No bioinformatics, programming, command line or single cell RNAseq analysis experience is expected. Previous experience using Galaxy is helpful but not required.
Learning Objectives
Understand the steps required in a typical single-cell RNA-Seq analysis
Determine and apply appropriate QC thresholds
Take a counts matrix, apply filtering, run UMAP and plot the results
Generate cell clusters and identify marker genes for cell type identification
Run a basic differential expression analysis
Understand the iterative nature of single-cell RNA-Seq analysis
Understand how single-cell RNA-Seq data and annotations can be saved in AnnData format and shared
Syllabus
Introduction to single-cell RNA-Seq analysis and Galaxy
QC and filter a counts matrix
Reduce dimensionality: PCA and UMAP
Clustering
Basic differential expression
Plotting and visualisations
Options for further analysis