Course Overview


Course Integrity

This course is compiled automatically on 2021-08-30

The course is tested and available on MacOS, Windows and Ubuntu Linux for R version 4.1.0 (2021-05-18)



Overview

In this course we are going to introduce basic analysis for single-cell RNAseq, with a specific focus on the 10X system. The course is divided into three sessions. In the first session, we will introduce how to interpret the Cell Ranger QC report and how to do analysis with the LOUPE Browser. We will also demonstrate the customized analysis we can support right know. In the Second session, we will demonstrate how to process scRNAseq data and make QC reports with Seurat. In the third session, we will discuss how to to do more advanced analysis and QC with Bioconductor packages.

Exercises and answer sheets are included to help you practice techniques and provide examples.

Course material and exercises are available to view as rendered HTML at https://rockefelleruniversity.github.io/scRNA-seq/. All material is available to download under GPL v2 license.



Setting up


System Requirements

Install R

R can be installed from the R-project website.

The R website can be found here http://www.r-project.org/.

The download links and associated installation instructions for multiple platforms can be found below provided by Revolution Analytics. https://cran.revolutionanalytics.com

We recommend installing R 4.1.0 as this is the version used to compile the course. Direct downloads for R 4.1.0 for the main platforms can be found below:


Install RStudio

RStudio can be installed from the RStudio website.

http://www.rstudio.com/

RStudio can be downloaded for all platforms at the link below

https://rstudio.com/products/rstudio/download/


Install required packages

From the course package

install.packages('BiocManager')
BiocManager::install('RockefellerUniversity/scRNA-seq',subdir='scRNASeq')


From CRAN and Bioconductor

install.packages('BiocManager')
BiocManager::install('DropletUtils')
BiocManager::install('scDblFinder')
BiocManager::install('SingleCellExperiment')
BiocManager::install('scran')
BiocManager::install('scater')
BiocManager::install('Seurat')
BiocManager::install('dplyr')
BiocManager::install('scuttle')
BiocManager::install('biomaRt')
BiocManager::install('knitr')
BiocManager::install('rmarkdown')
BiocManager::install('testthat')
BiocManager::install('yaml')


Download the material

Download the material




The Presentations


Single-cell RNA sequencing , Session 1

In this session we will cover the use of Cell Ranger and the LOUPE browser.

Single-cell RNA sequencing , Session 2

In this session we will cover data processing with Seurat, including:

  • Basic QC, including mitochondrial content and cell cycle
  • Normalization and clustering
  • Visualization

Single-cell RNA sequencing , Session 3

In this session we will cover data processing with Bioconductor pacakges, including:

  • Empty droplet removal
  • Ambient RNA removal
  • Doublet removal

Single-cell RNA sequencing , Session 4

In this session we will cover scRNA processing in python from the R session using the R reticulate package and the python AnnData and Scanpy packages:

  • Introduction to reticulate package.
  • Loading scRNA data to AnnData objects.
  • Processing scRNA as AnnData in Scanpy.
  • Export of Scanpy processed AnnData to Loom.
  • Import of Loom to SingleCellExperiment.

Getting help


Course help

For advice, help and comments for the material covered in this course please contact us at the issues page associated to this course.

The link to the help pages can be found here


General Bioinformatics support

If you would like contact us about general bioinformatics advice, support or collaboration, please contact us the Bioinformatics Resource Center at .