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Single Cell RNA-Seq Analysis with R Bioconductor (2-Part Series) Online
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.
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
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)
- Campus:
- Online
- Categories:
- Data Science Initiative > Bioinformatics and Statistics Data Science Initiative > Programming Data Science Initiative
- Online:
- This is an online event. Event URL will be sent via registration email.
