End-to-End Processing
Process single-cell RNA-seq data from raw reads to biologically interpretable results.
Accelerated Single-Cell Data Analysis
Techniques, applications, and interpretation. A practical course that takes teams from raw single-cell data to confident biological insight in under 3 hours.
What You Will Learn
Core capabilities your team builds during the session.
Method Selection
Select appropriate analysis methods and tools, including Seurat, Bioconductor, Scanpy, and ScarfWeb.
Quality Interpretation
Interpret quality control metrics, clustering outputs, and differential expression results with confidence.
Dataset Integration
Integrate multiple datasets and correct for batch effects across experiments.
Cell-Type Annotation
Annotate cell types confidently to uncover meaningful biological insights.
Course Outline
A structured 2.5-hour journey from raw data to publishable results.
Foundations
Introduction to single-cell RNA-seq, the data journey from sequencing to count matrices, and data upload on ScarfWeb. (35 min)
Hands-on Setup
Analysis configuration, parameter selection, and best practices for reproducible single-cell workflows. (20 min)
Break and Q&A
Open session with the instructors to discuss your own data and analysis questions. (10 min)
Deep Analysis
UMAP exploration, clustering, data quality assessment, batch effect correction, cell-type annotation, differential gene expression, and publishing your results. (55 min)
Who This Course Is For
Built for teams that need practical single-cell analysis fluency.
PhD Students and Postdocs
Build clear analysis instincts early and understand why each workflow step matters.
Experimental Researchers
Interpret outputs with confidence and connect single-cell results to biological decisions.
Bioinformatics and Core Facility Teams
Standardize best practices across projects and support users on reproducible workflows.
Course Instructors
Learn directly from domain experts in single-cell biology and computational genomics.
Goran Karlsson
Co-founder and Head of Partnerships, Nygen
PhD, Associate Professor in Molecular Hematology, Lund University.
Parashar Dhapola
Co-founder and CEO, Nygen
PhD, Computational Genomics.
Frequently Asked Questions
No. The course is completely free of charge. Nygen does not require the hosting facility to purchase or license any software.
None beyond a laptop with internet access. All analysis runs on ScarfWeb's cloud platform. No software installation is required.
All analysis is conducted on ScarfWeb's ISO 27001 certified, GDPR-compliant cloud infrastructure. There are no infrastructure demands on the hosting facility.
Approximately 2 hours and 30 minutes, including an interactive demo where participants can work with their own data.
The hosting facility should provide a conference room or lecture room suitable for the expected audience size.
Book this course for your institution
We bring the course to you. Free for core facilities, research groups, and academic institutions.
