Intro to Pathway Analysis

MSI Tutorial - Intro to Pathway Analysis

This tutorial covers the basics of pathway enrichment analysis and related techniques. It includes both a lecture section and a hands-on workshop section. The lecture portion covers the basics of over-representation analysis and gene set enrichment analysis and the requirements for each technique. Interpretation of summary statistics and guidelines for interpreting the graphics produced by pathway analysis tools are also covered. The hands-on workshop demonstrates how to use an MSI-developed software tool to run pathway analyses with the results of a real differential gene expression analysis. The tool is run via the command line, and an introduction to the command line is included. We also demonstrate how to use MSI’s Open OnDemand service to interact with MSI computing resources.

Prerequisites: Familiarity with genomics analyses, particularly RNA-seq. Linux command line experience is helpful but not necessary.

This tutorial will cover:

  • An overview of pathway enrichment and gene set enrichment analyses
  • Interpreting summary statistics and plots from commonly used software for pathway enrichment and gene set enrichment analyses
  • Common commands for the Linux command line
  • Basic organization of files and directories on Linux systems
  • Usage of an MSI-developed tool for pathway enrichment and gene set enrichment analyses
  • Launching a graphical desktop session on MSI HPC resources via Open OnDemand

To be successful, you should have:

  • An active MSI account
  • Basic understanding of genomics technologies, especially RNAseq

Date, time and location:

  • Apr. 9, 2024
  • 11:00am to 2:30pm
  • 575 Walter Library and online

Click here to Register


UPCOMING SESSIONS

Upcoming sessions

TUTORIAL INFORMATION

Tutorial Information

Recommended background: 

  • Informatics, Data Analysis

Training Level: 

  • Intermediate

Tutorial format: 

  • Lecture plus hands-on lab

Training Materials: 

  • Lecture Slides

Skills: 

  • Data Analysis

 

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