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Harnessing the power of single-cell transcriptomics is essential for uncovering the cellular heterogeneity at the heart of modern biological questions. Tailored for biologists with a foundational understanding of R, this course offers a structured, hands-on deep dive into scRNA-seq analysis.
Through a detailed R Markdown tutorial, you will learn to navigate the entire analytical pipeline—from initial quality control and normalization to dimensionality reduction (PCA/UMAP), cluster identification, and differential expression analysis. By the end of this course, you will have a robust, reproducible framework to transform complex raw sequencing data into clear, publication-ready biological insights.
Harnessing the power of single-cell transcriptomics is essential for uncovering the cellular heterogeneity at the heart of modern biological questions. Tailored for biologists with a foundational understanding of R, this course offers a structured, hands-on deep dive into scRNA-seq analysis.
Through a detailed R Markdown tutorial, you will learn to navigate the entire analytical pipeline—from initial quality control and normalization to dimensionality reduction (PCA/UMAP), cluster identification, and differential expression analysis. By the end of this course, you will have a robust, reproducible framework to transform complex raw sequencing data into clear, publication-ready biological insights.