WORKSHOP: Single Cell RNAseq analysis in R
This record includes training materials associated with the Australian BioCommons workshop ‘Single Cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 28- 29 July 2026.
Event description
Analysis and interpretation of single cell RNAseq (scRNAseq) data requires dedicated workflows. In this hands-on workshop we will show you how to perform single cell RNAseq analysis using Seurat, Harmony and Single R - R packages for QC, analysis, and exploration of single-cell RNAseq data.
We will discuss the ‘why’ behind each step and cover reading in the count data, quality control, filtering, normalisation, clustering, UMAP layout and identification of cluster markers. We will also explore various ways of visualising single cell expression data.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Lead trainers:
Dr Sarah Williams, QCIF Digital Research.
Fred Jaya, Sydney Informatics Hub, University of Sydney.
Facilitators:
Adele Barugahare, Monash Genomics and Bioinformatics Platform
Paul Harrison, Monash Genomics and Bioinformatics Platform
Infrastructure provision:
Dr Mitchell O'Brien, Sydney Informatics Hub, University of Sydney
Dr Giorgia Mori, Australian BioCommons
Coordination and host:
Dr Melissa Burke, Australian BioCommons
Training materials
This workshop follows materials collaboratively developed and maintained by Monash Genomics and Bioinformatics Platform, QCIF (bioinformatics), Sydney Informatics Hub and the Australian BioCommons.
Files and materials included in this record:
- Event metadata_scRNAseq2026 (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Materials shared elsewhere:
Training materials including detailed notes, exercises:
https://swbioinf.github.io/scRNAseq_Workshop/index.html
Rmd files of R code used during the workshop via GitHub: https://github.com/swbioinf/scRNAseq_Workshop
DOI: 10.5281/zenodo.21784360
Licence: Creative Commons Attribution 4.0 International
Keywords: Bioinformatics, scRNAseq, Single cell RNAseq
Status: Active
Activity log
