Description

This tutorial combines a lecture with a hands-on exercise to introduce the principles and workflows of single cell genomics data analysis. In the first part, attendees will learn about common experimental designs, data quality control metrics, commonly used software tools, and the general overview of the single cell analysis workflow. The second portion will be an interactive, hands-on tutorial in which participants will load and briefly explore a single cell dataset in both R and Python on the MSI system through Open On Demand (OOD). The aim is to help provide a starting point for new users to analyze single cell data using MSI resources. An experimental design questionnaire to help guide single cell genomics project design will also be presented.

This is a hybrid session with in person attendance in Walter Library 575 and online via Zoom.

This single-cell tutorial will cover:

• An introduction to single cell RNA-sequencing
• Basic experimental design principles and illustration of batch effects
• Common quality control metrics
• Common data analysis tools
• Basic data analysis workflow from FASTQ files to analysis-ready data
• A hands-on tutorial where we will familiarize ourselves with the OOD interface and use R and Python code to load and interact with a single-cell dataset

To be successful, you should have:

• A basic understanding of next-generation sequencing technology
• Familiarity with molecular biology and cell biology terminology
• A computer
• Connection to the UMN VPN (if attending from off campus)