Schedule - Introduction to scRNA-seq

Pre-reading

  1. Introduction to scRNA-seq
  2. Raw Data to Count Matrix
  3. Download this project

Day 1

Time Topic Instructor
09:30 - 09:45 Workshop Introduction Will
09:45 - 10:35 Bioinformatics begins at the bench:
How experimental decisions shape single-cell RNA-seq analyses		 Dr. Arpita Kulkarni
10:35 - 10:40 Break
10:40 - 11:00 scRNA-seq pre-reading discussion Noor
11:00 - 11:45 Quality Control Set-up Noor
11:45 - 12:00 Overview of self-learning materials and homework submission Will

Before the next class:

I. Please study the contents and work through all the code within the following lessons:

1. Cell Ranger Quality Summaries

Before you start any analysis, it’s important to know whether or not you have good quality cells. At these early stages you can flag or remove samples that could produce erroneous results downstream.

In this lesson, you will:

  • Discuss the outputs of CellRanger and how to run it
  • Review web summary HTML report
  • Create plots from metrics_summary.csv file

2. Theory of PCA

Before we can begin the next steps of the workflow, we need to make sure you have a good understanding of Principal Components Analysis (PCA). This method will be utilized in the scRNA-seq analysis workflow, and this foundation will help you better navigate those steps and interpretation of results.

In this lesson, you will:

  • Review the mathematical concepts behind PCA
  • Understand how PCA reduces dimensionality in high-throughput data
  • Interpret PCA plots in the context of scRNA-seq analysis
  1. Submit your work:
  • Each lesson above contains exercises; please go through each of them.
  • Submit your answers to the exercises using this Google form on the day before the next class.

Questions?

  • If you get stuck due to an error while runnning code in the lesson, email us

Day 2

Time Topic Instructor
09:30 - 10:00 Self-learning lessons discussion All
10:00 - 10:45 Quality Control with Additional Metrics Will
10:45 - 10:50 Break
10:50 - 11:40 Normalization, Variance, and PCA Noor
11:40 - 12:00 Introduction to Integration Theory Noor

Before the next class:

I. Please study the contents and work through all the code within the following lesson:

1. Running Integration and Complex Integration Tasks

In class, we described the theory of integration and in what situations we would implement it.

In this lesson, you will:

  • Run the code to implement CCA integration
  • Evaluate the effect of integration on the UMAP
  • Learn about methods for complex integration tasks (Harmonizing samples)

There are no exercises from this lesson, but please add any questions to this Google Formon the day before the next class.

Questions?

  • If you get stuck due to an error while runnning code in the lesson, email us

Day 3

Time Topic Instructor
09:30 - 10:00 Self-learning lessons discussion Noor
10:00 - 11:00 Clustering Noor
11:00 - 11:05 Break
11:05 - 12:00 Clustering Quality Control Will

Before the next class:

I. Please study the contents and work through all the code within the following lesson:

1. Seurat Cheatsheet

At this point, we have populated our Seurat object with many different pieces of information. Knowing how to access different values will allow you to interact more efficiently with your dataset.

In this lesson, you will:

  • Explore the different parts of a Seurat object
  • Use the built-in functions from the Seurat package for visualizations
  • Retrieve data efficiently from the Seurat object for downstream analyses
  1. Submit your work:
  • The lesson above contains exercises; please go through each of them.
  • Submit your answers to the exercises using this Google form on the day before the next class.

Questions?

  • If you get stuck due to an error while runnning code in the lesson, email us

Day 4

Time Topic Instructor
9:30 - 10:00 Self-learning lessons discussion All
10:00 - 11:00 Marker Identification Noor
11:00 - 11:10 Break
11:10 - 11:30 Workflow Summary Will
11:30 - 11:45 Overview and Final Q & A All
11:45- 12:00 Wrap Up Will

Other Relevant HBC Workshops

Resources

We have covered the analysis steps in quite a bit of detail for scRNA-seq exploration of cellular heterogeneity using the Seurat package. For more information on topics covered, we encourage you to take a look at the following resources:

Seurat-focused

Scaling up: scRNA-seq analysis on HPC

Cell type annotation

Highlighted papers

Other online scRNA-seq courses: