schedule

Schedule for the single-cell RNA-seq data analysis workshop

Pre-reading

• Introduction to scRNA-seq
• Raw data to count matrix
• Download this project

Day 1

Time	Topic	Instructor
09:30 - 09:45	Workshop introduction	Mary
09:45 - 11:00	Single-cell RNA-seq design and methods	Dr. Luciano Martelotto
11:00 - 11:05	Break
11:05 - 11:20	scRNA-seq pre-reading discussion	Meeta
11:20 - 12:00	Quality control set-up	Radhika

Before the next class:

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

   • Quality control
   • Overview of Clustering Workflow
   • Theory of Normalization and PCA
   • Normalization and regressing out unwanted variation

2. Complete the exercises:

   • Each lesson above contain exercises; please go through each of them.
   • Copy over your R code from the exercises to this (downloadable) R script
   • Upload the saved R script file to Dropbox day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

---

Day 2

Time	Topic	Instructor
09:30 - 10:40	Self-learning lessons discussion	Meeta/Radhika
10:40 - 10:45	Break
10:45 - 12:00	Integration	Mary

Before the next class:

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

   • Clustering
   • Clustering quality control
   • Marker identification

2. Complete the exercises:

   • Each lesson above contain exercises; please go through each of them.
   • Copy over your R code from the exercises to this (downloadable) R script
   • Upload the saved R script file to Dropbox day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

---

Day 3

Time	Topic	Instructor
09:30 - 10:30	Self-learning lessons discussion	All
10:30 - 10:40	Workflow summary	Meeta
10:40 - 10:45	Break
10:45 - 11:30	Discussion, Final Q & A	All
11:30 - 12:00	Wrap up	Mary

---

Answer Keys

• Answer key - assignment #1
• Answer key - assignment #2

---

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 vignettes
• Seurat cheatsheet
• Satija Lab: Single Cell Genomics Day
• "Principal Component Analysis (PCA) clearly explained", a video from Josh Starmer
• Additional information about cell cycle scoring
• Using R on the O2 cluster
• Highlighted papers for sample processing steps (pre-sequencing):
  • "Sampling time-dependent artifacts in single-cell genomics studies." Massoni-Badosa et al. 2019
  • "Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses." O'Flanagan et al. 2020
  • "Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows." Denisenko et al. 2020

Building on this workshop

• Other online scRNA-seq courses:

  • http://bioconductor.org/books/release/OSCA/
  • https://liulab-dfci.github.io/bioinfo-combio/
  • https://hemberg-lab.github.io/scRNA.seq.course/
  • https://github.com/SingleCellTranscriptomics
  • https://broadinstitute.github.io/2020_scWorkshop/

• Resources for scRNA-seq Sample Prep:

  • https://www.protocols.io/
  • https://support.10xgenomics.com/single-cell-gene-expression/sample-prep
  • https://community.10xgenomics.com/

Other helpful links

• Online learning resources
• All hbctraining training materials