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	Meeta
09:45 - 10:00	scRNA-seq pre-reading discussion	Mary
10:00 - 10:40	Quality control set-up	Radhika
10:40- 10:45	Break
10:45 - 11:00	Overview of self-learning materials and homework submission	Meeta
11:00 - 12:00	Single-cell RNA-seq design and methods	Dr. Mandovi Chatterjee

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.

3. Run the code in this script to perform the steps of integration. We will discuss the code and theory in 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.

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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.

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Day 3

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

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Answer Keys

• Assignment #1
  • QC
  • SCT and regressing out unwanted variation
• Answer key - assignment #2

Downstream analyses

Differential expression between conditions

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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
• Azimuth reference-based analysis
• CellMarker resource
• Highlighted papers for single-nuclei RNA-seq:
  • Single-nucleus and single-cell transcriptomes compared in matched cortical cell types
  • A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors
• Ligand-receptor analysis with CellphoneDB

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/
  • https://nbisweden.github.io/workshop-scRNAseq/schedule.html

• 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