Introduction to Spatial Single-cell RNA-seq Schedule

Pre-reading

Day 1

Time	Topic	Instructor
09:30 - 09:45	Workshop introduction	Will
09:45 - 10:45	Introduction to Spatial Single Cell RNA-sequencing	Dr. Mandovi Chatterjee
10:45 - 10:50	Break
10:50 - 11:15	scRNA-seq pre-reading discussion	All
11:00 - 11:45	Loading Spatial Data	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:

Quality Control

Click here for a preview of this lesson

Brief description of the lesson

In this lesson you will:
- LO 1
- LO 2
- LO 3
Theory of PCA

Click here for a preview of this lesson

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.

Submit your work:

Each lesson above contains exercises; please go through each of them.
Submit your answers to the exercises using this Google form(NEED LINK STILL) on the day before the next class.

Questions?

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

Day 2

Time	Topic	Instructor
09:30 - 10:00	Self-learning lessons discussion	All
10:00 - 11:00	Normalization and Sketch Downsampling	Noor
11:00 - 11:05	Break
11:05 - 12:00	scRNA-seq Workflow	Will

Before the next class:

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

Integration
Spatially Derived Clusters

Click here for a preview of this lesson

Brief description of the lesson

In this lesson you will:
- LO 1
- LO 2
- LO 3

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: analysis on HPC

Using RStudio on O2
- HMSRC wiki page
- HBC RStudio on O2 tutorial

Highlighted papers

Other online courses:

--- title: Introduction to Spatial Single-cell RNA-seq Schedule sidebar: false toc: false execute: eval: false --- ## Pre-reading - [Spatial Technology Overview](../lessons/spatial_technology_overview.qmd) - [Pre-reading 2](../lessons/Pre-reading_02.qmd) - [Pre-reading 3](../lessons/Pre-reading_03.qmd) ## Day 1 | Time | Topic | Instructor | |:-----------:|:----------:|:--------:| | 09:30 - 09:45 | [Workshop introduction](../slides/workshop_intro_slides.pdf) | Will | | 09:45 - 10:45| [Introduction to Spatial Single Cell RNA-sequencing](../lessons/01_introduction-to-spatial.qmd) | [Dr. Mandovi Chatterjee](https://singlecellcore.hms.harvard.edu/people/mandovi-chatterjee) | | 10:45 - 10:50 | Break | | 10:50 - 11:15 | scRNA-seq pre-reading discussion | All | | 11:00 - 11:45 | [Loading Spatial Data](../lessons/02_loading-spatial-data.qmd) | 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. [Quality Control](../lessons/03_quality-control.qmd) <details> <summary>Click here for a preview of this lesson</summary> Brief description of the lesson In this lesson you will: - LO 1 - LO 2 - LO 3 </details> 2. [Theory of PCA](../lessons/04_theory_of_PCA.qmd) <details> <summary>Click here for a preview of this lesson</summary> 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. </details> II. **Submit your work**: * Each lesson above contains exercises; please go through each of them. * **Submit your answers** to the exercises using [this Google form]()(**NEED LINK STILL**) on **the day *before* the next class**. ### Questions? * ***If you get stuck due to an error*** while running code in the lesson, [email us](mailto:hbctraining@hsph.harvard.edu) *** ## Day 2 | Time | Topic | Instructor | |:-----------:|:----------:|:--------:| | 09:30 - 10:00 | Self-learning lessons discussion | All | | 10:00 - 11:00| [Normalization and Sketch Downsampling](../lessons/05_normalization_and_sketch_downsampling.qmd) | Noor | | 11:00 - 11:05 | Break | | 11:05 - 12:00| [scRNA-seq Workflow](../lessons/06_scRNAseq_workflow.qmd) | Will | ### Before the next class: I. Please **study the contents** and **work through all the code** within the following lessons: 1. [Integration](../lessons/07_integration.qmd) 2. [Spatially Derived Clusters](../lessons/08_spatially_derived_clusters.qmd) <details> <summary>Click here for a preview of this lesson</summary> Brief description of the lesson In this lesson you will: - LO 1 - LO 2 - LO 3 </details>                                                 *** ## 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 * [Seurat vignettes](https://satijalab.org/seurat/vignettes.html) * [Seurat cheatsheet](https://satijalab.org/seurat/essential_commands.html) * [Satija Lab: Single Cell Genomics Day](https://satijalab.org/scgd21/) ### Scaling up: analysis on HPC * Using RStudio on O2 * [HMSRC wiki page](https://harvardmed.atlassian.net/wiki/spaces/O2/pages/1623425967/RStudio+on+O2) * [HBC RStudio on O2 tutorial](https://hbctraining.github.io/Intro-to-Unix-QMB/lessons/R_studio_on_02.html) ### Highlighted papers ### Other online courses: