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Single Cell RNA-Seq Analysis with R Bioconductor (2-Part Series) Online


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.


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

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


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


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

Related LibGuide: Bioinformatics and Statistics Resources by Karla Lindquist

Dates & Times:
3:00pm - 5:00pm, Tuesday, Mar 30 2021
3:00pm - 5:00pm, Wednesday, Mar 31 2021
Time Zone:
Pacific Time - US & Canada (change)
  Data Science Initiative > Bioinformatics and Statistics     Data Science Initiative > Programming     Data Science Initiative  
This is an online event. Event URL will be sent via registration email.

Registration is required. There are 0 seats available.

Event Organizer

Profile photo of Karla Lindquist
Karla Lindquist