Single-cell RNA-Seq Analysis (SCRN03) – Applications for Evolutionary Biology
 https://prstats.org/course/single-cell-rna-seq-analysis-scrn03/
Delivered by experienced bioinformaticians with expertise in single-cell transcriptomics, RNA sequencing, and computational biology.
Learn how to analyse single-cell RNA sequencing (scRNA-seq) data in R using Seurat, with methods that are increasingly relevant to evolutionary biology, evolutionary developmental biology, and comparative genomics.
Single-cell transcriptomics makes it possible to study gene expression at the level of individual cells, revealing cellular diversity and regulatory variation that are often hidden in bulk RNA-Seq data. These approaches are opening new opportunities to investigate the evolution of cell types, developmental pathways, phenotypic diversity, adaptation, and gene regulation across populations and species. This hands-on course provides practical training in modern scRNA-seq workflows, including quality control, normalisation, clustering, dimensionality reduction, differential expression, and cell type identification.
What you'll gain
- A strong understanding of single-cell RNA-Seq technologies and experimental design
- Practical experience analysing scRNA-seq datasets using Seurat in R
- Skills in quality control, normalisation, clustering, dimensionality reduction, and cell type annotation
- Understanding of differential expression analysis and downstream biological interpretation
- Confidence applying single-cell transcriptomics to evolutionary research
Course format
- Live, instructor-led online training
- Hands-on coding with real single-cell RNA-Seq datasets
- Interactive practical exercises throughout
- Strong focus on applied, research-ready workflows
Who is this course for?
- Evolutionary biologists and evolutionary developmental biologists
- Comparative genomic and transcriptomic researchers
- Population geneticists and molecular evolution researchers
- Bioinformaticians and computational biologists
- PhD students and quantitative life scientists
Why take this course?
Single-cell transcriptomics is becoming an important tool for studying how cellular functions, developmental programmes, and gene regulatory systems evolve. By comparing gene expression across cell types, tissues, populations, or species, researchers can investigate cell-type evolution, developmental divergence, adaptive responses, and the molecular basis of phenotypic innovation.
This course equips you with the practical skills needed to process, analyse, visualise, and interpret single-cell RNA-Seq data using modern R-based workflows. Whether you're studying the evolution of cell types, developmental systems, gene regulation, adaptation, comparative physiology, or non-model organisms, you'll gain the analytical toolkit needed to apply single-cell transcriptomics confidently to evolutionary research.
Learn more & enrol
PR Stats course page for Single-cell RNA-Seq Analysis (SCRN03)
https://prstats.org/course/single-cell-rna-seq-analysis-scrn03/
Questions?
Email: oliver@prstats.org

Oliver Hooker
Managing Partner

Advanced Training for Researchers in the Life Sciences
coursesinfo@prstats.org | www.prstats.org

(to subscribe/unsubscribe the EvolDir send mail to
evoldir@evoldir.net)