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Single-cell RNA-seq analysis workshop

Description

This repository has teaching materials for a 2-day, hands-on Introduction to single-cell RNA-seq analysis workshop. This 2-day hands-on workshop will instruct participants on how to design a single-cell RNA-seq experiment, and how to efficiently manage and analyze the data starting from count matrices. This will be a hands-on workshop in which we will focus on using the Seurat package using R/RStudio. Working knowledge of R is required or completion of the Introduction to R workshop.

Learning Objectives

• Undertand the considerations when designing a single-cell RNA-seq experiment
• Discuss the steps involved in taking raw single-cell RNA-sequencing data and generating a count (gene expression) matrix
• Compute and assess QC metrics at every step in the workflow
• Cluster cells based on expression data and derive the identity of the different cell types present
• Perform integration of different sample conditions

These materials are developed for a trainer-led workshop, but also amenable to self-guided learning.

Lessons

Click here for links to lessons and proposed schedule

Installation Requirements

Applications

Download the most recent versions of R and RStudio for your laptop:

• R (version 3.6.0 or above)
• RStudio

Packages for R

Note 1: Install the packages in the order listed below.

Note 2:  When installing the following packages, if you are asked to select (a/s/n) or (y/n), please select “a” or "y" as applicable.

Note 3: All the package names listed below are case sensitive!

(1) Install the 10 packages listed below from CRAN using the install.packages() function.

1. tidyverse
2. Matrix
3. RCurl
4. scales
5. cowplot
6. devtools
7. BiocManager
8. Seurat**

Please install them one-by-one as follows:

install.packages("tidyverse")
install.packages("Matrix")
install.packages("RCurl")
& so on ...

** If you have trouble installing Seurat, please install multtest using the following lines of code, then try installing Seurat again:

install.packages("BiocManager")

BiocManager::install("multtest")

(2) Install the 4 packages listed below from Bioconductor using the the BiocManager::install() function.

1. SingleCellExperiment
2. AnnotationHub
3. ensembldb

Please install them one-by-one as follows:

BiocManager::install("SingleCellExperiment")
BiocManager::install("AnnotationHub")
& so on ...

(3) Finally, please check that all the packages were installed successfully by loading them one at a time using the library() function.

library(Seurat)
library(tidyverse)
library(Matrix)
library(RCurl)
library(scales)
library(cowplot)
library(SingleCellExperiment)
library(AnnotationHub)
library(ensembldb)

(4) Once all packages have been loaded, run sessionInfo().

sessionInfo()

These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.