The Single-Cell RNA-Seq (scRNA-Seq) Crash Course provides an intensive, hands-on introduction to single-cell transcriptomics — one of the most advanced areas in genomics research. This program focuses on understanding cellular heterogeneity, data preprocessing, clustering, and visualization using real-world single-cell datasets.
Designed for students, researchers, and professionals in life sciences, this crash course offers a step-by-step understanding of scRNA-Seq analysis using powerful bioinformatics tools and pipelines.
Introduction to scRNA-Seq & Applications – Understand the principles, workflow, and biological significance of single-cell RNA sequencing.
Linux Setup & Tool Installation – Learn to set up and configure the Linux environment for scRNA-Seq data processing.
Preprocessing & Quality Control – Perform cell- and gene-level quality checks, normalization, and data filtering.
Clustering & Differential Expression – Identify cell clusters, detect marker genes, and perform differential gene expression analysis.
Understand the fundamentals and workflow of single-cell RNA sequencing analysis.
Perform preprocessing and quality control of scRNA-Seq data using bioinformatics tools.
Cluster cells and identify marker genes for distinct cell populations.
Visualize and interpret single-cell data using dimensional reduction techniques like t-SNE and UMAP.
Gain practical experience in analyzing real scRNA-Seq datasets for research and publication-ready
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5-Day Hands-on Crash Course on Single-Cell Genomics and Transcriptomics: From Data to Discovery
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