Single-Cell RNA-Seq Analysis with R
Bioinformatics
R
Transcriptomics
Course Description
The Single-Cell RNA-Seq Analysis with R course is designed for researchers and bioinformaticians interested in unlocking insights from single-cell transcriptomics data using the R programming language. Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and gene expression dynamics. This course provides a comprehensive overview of scRNA-seq data analysis, covering preprocessing, quality control, dimensionality reduction, cell clustering, differential expression analysis, and visualization techniques.
Learning Objectives
By the end of the Single-Cell RNA-Seq Analysis with R course, participants will be able to:
- Introduction to Single-Cell RNA-Seq
- Preprocessing and Quality Control
- Dimensionality Reduction Techniques
- Cell Clustering and Annotation
- Differential Expression Analysis
- Trajectory Analysis and Pseudotime
- Functional Enrichment Analysis
- Data Visualization
- Integration with Other Omics Data
- Interpreting Results and Reporting