Single-cell RNA Sequence Analysis

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General Information

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 involve 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. 10X Genomics is a market leader in the single cell space and was among the first technologies that made it feasible to profile thousands of cells simultaneously. Single cell technology is changing rapidly and it is not clear whether any other companies will be able to successfully challenge 10X’s dominance in this space.

Who: The course is aimed at researchers who want to employ single-cell RNA sequence analysis for resolving cell heterogeneity by exploring gene expression profiles at a single-cell resolution.

Prerequisites: R programming skills are required for successful participation. If you can manipulate R data structures (e.g. lists, matrices, data frames) you are ready for this course. Knowledge of genetics and statistics will also help you gain the most from this course. To ensure that all participants receive the support that they need during training, remote participation will not be made available. You must attend in person and on-site.

Where: 600 Main Street, Bar Harbor, Maine. Get directions with OpenStreetMap or Google Maps.

When: Dec 1-2, 2022. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have a few specific software packages installed (listed below).

Accessibility: We are committed to making this workshop accessible to everybody. For workshops at a physical location, the workshop organizers have checked that:

• The room is wheelchair / scooter accessible.
• Accessible restrooms are available.

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email susan.mcclatchy@jax.org for more information.

Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.

Collaborative Notes

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.

Surveys

Please be sure to complete this survey after the workshop.

Post-workshop Survey

Schedule

Setup

To participate in a workshop, you will need access to software as described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

Install packages

Install tidyverse, Matrix, Seurat and BiocManager packages from the RStudio Packages tab or by copy-pasting the following in the Console. Once BiocManager is installed load SingleCellExperiment, scds and harmony from Bioconductor.

install.packages(c("tidyverse", "Matrix", "Seurat", "BiocManager", "harmony",
                   "enrichR"), dependencies = TRUE)
BiocManager::install(c("SingleCellExperiment", "scds", "DESeq2"))

Once the installation has finished, load the libraries to verify that all packages installed correctly.

library(tidyverse)
library(Matrix)
library(Seurat)
library(harmony)
library(enrichR)
library(SingleCellExperiment)
library(scds)
library(DESeq2)

Data files and project organization

1. Create a new project called scRNA.
   • Click the File menu button, then New Project.
   • Click New Directory.
   • Click New Project.
   • Type scRNA as the directory name. Create the project anywhere you like, but don’t forget where you put it!
   • Click the Create Project button. This will create a file called scRNA.Rproj in the directory you just created. In the future you can double-click on this file to open RStudio in this directory. This will be the easiest way to interact with the files/code you produce in this workshop.
2. Use the Files tab to create a data folder to hold the data, a scripts folder to house your scripts, and a results folder to hold results. Alternatively, you can copy and paste the following commands into the R console for step 2 only. You still need to create a project with step 1.

dir.create("data")
dir.create("scripts")
dir.create("results")

Data Download

Open the scRNA.Rproj project. Before the workshop, please download the following files:

download.file(url = 'https://thejacksonlaboratory.box.com/shared/static/vfe1bwyqtypxs6p5k4z0cw7z7jczyan1.zip', 
              destfile = 'data/mouseStSt_exvivo.zip',
              method   = 'curl', 
              extra    = ' -L ')
download.file(url = 'https://thejacksonlaboratory.box.com/shared/static/b153ueu2lie3st760maj4zr9u0vp7o2t.zip', 
              destfile = 'data/mouseStSt_invivo.zip',
              method   = 'curl', 
              extra    = ' -L ')
download.file(url = 'https://thejacksonlaboratory.box.com/shared/static/yx64wion3etmbidtt4bm2nbl1yyceptn.txt',
              destfile = 'data/regev_lab_cell_cycle_genes_mm.fixed.txt',
              method   = 'curl', 
              extra    = ' -L ')
unzip(zipfile = 'data/mouseStSt_invivo.zip' ,
      exdir   = 'data')
unzip(zipfile = 'data/mouseStSt_exvivo.zip',
      exdir   = 'data')