Peer-to-Peer Teaching Series- Single-Cell RNA-Seq Data Analysis and Visualization Using R: A Hands-On Workshop
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Peer-to-Peer Teaching Series- Single-Cell RNA-Seq Data Analysis and Visualization Using R: A Hands-On Workshop In-Person
Presenter: Upasna Srivastava, PhD
Omics data is revolutionizing biological research, providing deeper insights into cellular diversity and function. Single-cell RNA sequencing (scRNA-seq) enables the study of gene expression at the individual cell level, offering a more detailed view of heterogeneity within tissues or organisms.
In this session, you will learn how to analyze 10X Chromium single-cell RNA-seq data using Seurat, a widely used R package for scRNA-seq analysis. This hands-on workshop will guide you through key steps in data processing, analysis, and visualization, helping you extract meaningful biological insights from your dataset.
You will learn how to:
- Import and preprocess 10X Genomics single-cell RNA-seq data in R.
- Perform quality control, normalization, and scaling to prepare data for analysis.
- Apply dimensionality reduction techniques (PCA, t-SNE, UMAP) to visualize cellular diversity.
- Identify distinct cell populations using clustering algorithms.
- Conduct differential expression analysis to find marker genes.
- Annotate cell types using known markers or automated tools.
- Hands-on Q&A and Discussion
- Generate insightful visualizations, including:
- UMAP/t-SNE plots for cell clustering
- Feature plots, violin plots, and dot plots for gene expression analysis
- Heatmaps for differentially expressed genes
- Integrate results into RMarkdown for reproducible reporting.
Requirements:
Laptop is required for this hands-on workshop with R ≥4.0, RStudio, and Seurat installed
Basic knowledge of R and RStudio is recommended.
Before attending, please install the following R packages:
-
Seurat
-
dplyr
-
ggplot2
Scripts and example datasets will be provided before the workshop
Target Audience:
This workshop is ideal for biologists, bioinformaticians, and computational researchers who want to gain hands-on experience with single-cell RNA-seq analysis. Whether you are new to scRNA-seq or looking to refine your skills, this session will provide practical guidance for working with Seurat.
Registration is required to attend.
- Date:
- Thursday, April 10, 2025
- Time:
- 10:00am - 12:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Location:
- SHM L 111, Cushing/Whitney Medical Library, 333 Cedar Street
- Campus:
- Medical School
- Categories:
- Bioinformatics