- This event has passed.
Single-Cell RNA-Seq Data Analysis
Learn the fundamentals of Single-Cell RNA-Seq Data Analysis with hands-on experience
9
20+
10
3
When and How
Start Date
26th of January 2025
Duration
1.5 – 2 hours per week
Online
via zoom
Overview
Join BioCompiler’s Comprehensive Single-Cell RNA-Seq (scRNA-Seq) Data Analysis Workshop and elevate your bioinformatics expertise to new heights!
Why Single-Cell RNA-Seq Matters?
Single-cell RNA sequencing is revolutionizing biology by allowing researchers to explore gene expression at the resolution of individual cells. This cutting-edge technology is key to uncovering cellular diversity, understanding developmental processes, and advancing disease research.
After completing this workshop, you will be able to:
- Understand scRNA-Seq Basics: Grasp the principles of single-cell transcriptomics and its applications in biological research.
- Gain Confidence in R Programming: Learn the fundamentals of R programming for data manipulation and visualization in bioinformatics workflows.
- Master Data Preprocessing: Perform essential preprocessing steps, including quality control, filtering, and normalization of scRNA-Seq data.
- Analyze Clusters and Marker Genes: Identify cell populations, detect differentially expressed genes, and interpret biological pathways.
- Visualize Cellular Landscapes: Create informative plots, such as t-SNE, UMAP, and heatmaps, to represent single-cell data effectively.
- Perform Advanced Analysis: Explore trajectory inference, pseudotime analysis, and integrative workflows for multi-omics data.
- Apply Reproducible Workflows: Implement best practices for scalable, robust, and reproducible scRNA-Seq analysis.
This workshop provides you with the tools to tackle real-world single-cell projects and derive actionable biological insights.
Content
1️⃣ Introduction to R for Bioinformatics – 2 Sessions
Build a solid foundation in R programming:
- Session 1: Introduction to R and RStudio
- Session 2: Data Manipulation and Visualization in R
2️⃣ Introduction to Single-Cell Transcriptomics – 2 Sessions
Explore the fundamentals of scRNA-Seq:
- Session 1: Overview of Single-Cell Technologies and Experimental Design
- Session 2: Understanding Raw Data and File Formats
3️⃣ Preprocessing and Quality Control – 2 Sessions
Learn to preprocess your data for meaningful analysis:
- Session 1: Quality Control and Filtering Metrics
- Session 2: Normalization and Scaling Techniques
4️⃣ Dimensionality Reduction and Clustering – 1 Sessions
Uncover cellular diversity with clustering and visualization:
- Session 1: Principal Component Analysis (PCA) and Feature Selection, t-SNE and UMAP for Data Visualization and Cell Clustering and Marker Gene Identification
5️⃣ Downstream and Advanced Analysis – 2 Sessions
Extract deeper biological insights from scRNA-Seq data:
- Session 1: Differential Gene Expression (DGE) Analysis and cell type annotation.
- Session 2: Pseudotime and Trajectory Analysis, Multi-Omics Integration with scRNA-Seq and Final Project
This workshop is ideal for:
- Researchers interested in single-cell biology and transcriptomics.
- Bioinformaticians eager to explore cellular heterogeneity.
- Professionals aiming to expand their expertise in cutting-edge genomics tools.
No matter your level, this workshop will empower you with essential tools and insights.
- Sessions are recorded, so you can revisit the content anytime.
- Interactive Q&A after each session ensures personalized support.
- Flexible timing to accommodate participants from different time zones
Google 
Google 