Single Cell RNAseq

Single cell RNA-sequencing (scRNA-Seq) is a method of quantifying transcript expression levels in individual cells. scRNA-Seq technology can take on many different forms and this area of research is rapidly evolving. In 2022, the most widely used systems for performing scRNA-Seq involved separating cells and introducing them into a microfluidic system which performs the chemistry on each cell individually (droplet-based scRNA-Seq).

In this workshop we will primarily focus on the 10X Genomics technology. We will review the steps in single cell isolation and library preparation. We will then work with gene count data produced by CellRanger and will proceed through filtering, normalization, selection of variable genes, clustering, and finding marker genes for each cluster. Each student will analyze the data on their laptop.

Prerequisites

  • Basic knowledge of R.
  • Basic understanding of cellular and molecular biology.
  • Understanding of bulk RNA-sequencing.

Schedule

Setup Download files required for the lesson
00:00 1. Introduction to Single Cell RNA-seq What is single cell RNA-seq?
What is the difference between bulk RNA-seq and single cell RNA-seq?
How do I choose between bulk RNA-seq and single cell RNA-seq
00:55 2. Experimental Considerations How do I design a rigorous and reproducible single cell RNAseq experiment?
01:45 3. Overview of scRNA-seq Data What does single cell RNA-Seq data look like?
03:45 4. Quality Control of scRNA-Seq Data How do I determine if my single cell RNA-seq experiment data is high quality?
What are the common quality control metrics that I should check in my scRNA-seq data?
05:45 5. Common Analyses What are the most common single cell RNA-Seq analyses?
07:55 6. Biology Driven Analyses of scRNA-Seq What are some scRNA-Seq analyses that might provide me with biological insight?
10:05 7. Analyzing Your Data Can I analyze my own single cell RNA-Seq experiment?
11:10 8. Future Directions What are some important concepts from the single cell field that we did not have time to discuss in this course?
What are some interesting future research directions in areas related to single cell transcriptomics?
11:40 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.