Processing and Interpreting Single Cell RNA-seq Data
This is a one day short-course that also has a pre-workshop component. Limited seating is available for this course.
This one-day short course is designed to provide participants with practical skills in bioinformatics and statistical methods for the analysis of single cell RNA sequencing (scRNA-seq) data. The course will cover key steps in scRNA-seq analysis primarily using the R package Seurat, with a focus on data preprocessing, quality control, dimensionality reduction, and clustering. Methods in exploratory analysis, dataset integration, differential gene expression, and pseudotime analysis will also be explored. Participants should expect to develop a broad familiarity of the basics in scRNA-Seq analysis and acquire the knowledge to understand and utilize more advance methods for their research application.
Prior to taking this course, participants need to complete the course preparation module (M0), which will instruct them how to install and test all the required software. A link will be posted here 2 weeks before the course start date to the course preparation instructions.
- Date: Saturday, April 6, 2024
- Time: 8 a.m. to 5 p.m.
- Location: Talley Student Union, Rm 4280
Instructors
Bruce Allen Corliss, Ph.D.
Allison Dickey, Ph.D.
Start | End | Program |
---|---|---|
8am | 8:30am | Arrival |
8:30am | 9:15am | Welcome and Intro to scRNA |
9:15am | 10:30am | scRNA-Seq Preprocessing and Alignment with Cell Ranger |
10:30am | 10:45am | BREAK |
10:45am | 12pm | Standard scRNA-Seq Processing with Seurat, Part 1 |
12pm | 12:45pm | LUNCH |
12:45pm | 1:15pm | Standard scRNA-Seq Processing with Seurat, Part 2 |
1:15pm | 2pm | Methods in scRNA-Seq Cell Type Identification |
2pm | 3pm | Dataset Integration, DGE, and Exploratory Analysis with Seurat |
3pm | 3:15pm | BREAK |
3:15PM | 4:15PM | Pseudotime Analysis with Monocle3 |
4:15PM | 5PM | Best Practices, Troubleshooting, Q & A |