Why this course?
This comprehensive single-cell RNA-Seq and multi-omics analysis course is designed to deliver actionable insights in a fraction of the time other multi-day workshops require.
Who is this for?
This course is ideal for PhD students, experimental researchers, bioinformaticians, and anyone looking to gain fluency in single-cell transcriptomics and multi omics research.
Course outline:
Part 1 (No UMAPs yet)
000-005 - Intro
005-020 - Single-cell RNA-Seq Data Journey
020-035 - Data upload on Nygen
030-055 - Analysis setup and best practices
055-065 BREAK (Q&A session open)
Part 2 (UMAPs and beyond)
065-075: Data eploration: UMAPs, clusters
075-085: Data quality, batch effect
085-095: Cell type annotation
090-105: Cell selections and diff. gene. ep.
105-115: Publishing data
115-120: Wrap-up
Learning Outcomes
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Process single-cell RNA-seq data from raw reads to biologically interpretable results
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Select appropriate analysis methods and tools (Seurat, Bioconductor, Scanpy, or Nygen)
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Interpret quality control metrics, clustering outputs, and differential expression results
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Integrate multiple datasets and correct for batch effects
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Annotate your data confidently to uncover meaningful biological insights