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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
- Load and inspect scRNA-seq data with R and Seurat
- Understand the fundamental steps of preprocessing and quality control
- Prepare data for analysis by normalizing, scaling and filtering data
- Identify principal components that identify variability and perform non-linear dimension reduction (UMAP and tSNE)
- Categorize cell types through clustering and visualize results
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
- 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
- Online:
- This is an online event. Event URL will be sent via registration email.
- Categories:
- Data Science > Bioinformatics and Statistics Data Science > Programming Data Science
