Overview

In this workshop, we will demonstrate how to process and analyze single cell RNA-seq data using R Bioconductor packages, focusing primarily on seurat. It is intended for those with intermediate R programming skills who are familiar with the biological concepts of single cell RNA-seq.

Learning Objectives

• Be aware of different methods of loading scRNA-seq data into R
• Understand the fundamental steps of preprocessing and quality control
• Identify principal components that identify variability
• Categorize cell types through clustering
• Perform non-linear dimension reduction for final evaluation and visualization (e.g. via tSNE and UMAP graphs)

Prerequisites / Preparation

To benefit from this workshop, you should at minimum be comfortable with the materials covered in our Introduction to R Programming or Software Carpentry workshops.

In addition, you will need to install the software and R packages required prior to the workshop, as described below.

Software

Please install the following software on your laptop prior to the workshop.

R

R Bioconductor

RStudio

We will send specific package installation instructions by email about a week in advance of the workshop. 

Materials

Workshop materials will be available online by the time of the workshop here.

Instructors

Angelo Pelonero, Instructional Designer, UCSF Library Data Science Initiative and Bakar Computational Health Sciences Institute

Rebecca Jaszczak, PhD Candidate, UCSF Biomedical Sciences Program

Karla Lindquist, PhD, is the Scientific Lead for the UCSF Library Data Science Initiative