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Course Description

The CBW has developed a 2.5-day course covering the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information. The workshop focuses on the principles and concepts required for analyzing and conducting pathway and network analysis on a gene list from any organism, although focus will be on human and model eukaryotic organisms.

Course Objectives

Participants will gain practical experience and skills to be able to:

  • Get more information about a gene list;
  • Discover what pathways are enriched in a gene list (and use it for hypothesis generation);
  • Find out how a set of genes is connected by e.g. protein interactions and identify pathways, systems and modules within this network;
  • Predict gene function and extend a gene list;
  • Identify master regulators, such as transcription factors, active in the experiment.

We will develop a unified analysis flow chart throughout the course that students will be able to follow after the workshop to conduct their own analysis.

Target Audience

This workshop is intended for biologists working with ‘Omics data’ (e.g. gene expression, protein expression, molecular interactions, large-scale genetic screens and other omics data) from human and model eukaryotic organisms who are interested in interpreting large gene lists resulting from their experiments. Concepts will be applicable to omics data from non-eukaryotic organisms, but software and demonstrations will not cover them.


You will also require your own laptop computer. Minimum requirements: 1024×768 screen resolution, 1.5GHz CPU, 2GB RAM, 10GB free disk space, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements). If you do not have access to your own computer, please contact for other possible options.

This workshop requires participants to complete pre-workshop tasks and readings.

Course Outline

Module 1: Introduction to pathway and network analysis (Gary Bader)

  • Where gene lists come from and what they are useful for
  • Pathway and network analysis overview
  • Workflow of concepts and tools from gene list to pathway analysis
  • Examples of multiple paths through the workflow that will be covered in the workshop
  • Sources of pathway and network information: GO biological process, network databases, pathway databases. Examples of pros and cons of each type of information
  • General issues: gene identifiers, data normalization

Module 2: Finding over-represented pathways in gene lists (Veronique Voisin)

  • Statistics for detecting over-representation e.g. hypergeometric test, GSEA
  • Multiple testing correction: Bonferroni, Benjamini-Hochberg FDR
  • Filtering Gene Ontology e.g. using evidence codes

Lab Practical: Performing over-representation analysis

  • Workflow of tools and steps
  • g:Profiler tool for over-representation analysis
  • Gene Set Enrichment Analysis (GSEA) and Enrichment Maps software tool
  • Running gene enrichment tools on your gene list

Module 3: Network visualization and analysis with Cytoscape (Gary Bader)

  • Introduction to Cytoscape
  • Cytoscape demo

Lab Practical: Tutorials on Cytoscape

  • Layouts
  • Labels
  • EnrichmentMap

Module 4: More Depth on Pathway and Network Analysis (Lincoln Stein)

  • Basic network concepts
  • Types of pathway and network information
  • Network and pathway databases
  • More examples of pathway and network analysis methods
  • Reactome analysis tools: network clustering and paradigm

Lab Practical: Reactome (Robin Haw)

  • Workflow of tools and steps
  • Reactome FIViz Cytoscape app

Module 5: Gene Function Prediction (Sara Mostafavi)

  • Functional association networks and gene function prediction
  • Functional relationships, similarity space
  • Guilt-by-association concept
  • GeneMANIA and STRING tools

Lab Practical

  • Workflow of tools and steps
  • Using GeneMANIA to assess gene and gene list function

Module 6: Regulatory Network Analysis (Michael Hoffman)

  • Overview of transcription and transcriptional regulation
  • Data sources for regulatory data – ChIP-seq, DNAse-seq, methylation data
  • Using epigenomics data
  • Finding transcription factor binding sites

Lab Practical

  • Analysis of Enriched Transcription Factor Motifs with iRegulon

Integrated Assignment: Part 1

  • Enrichment analysis using GSEA and g:Profiler

Integrated Assignment Part 2

  • Reactome FIViz Cytoscape app and GeneMANIA

Workshop Details:

Duration: 3 days

Start: Jun 26, 2019

End: Jun 28, 2019

Location: Toronto, Ontario Canada
Course Mode:

Status: Registration Closed

Workshop Ended

for applications received between to
Limited to: 30 participants
Open Access Content:

Canadian Bioinformatics Workshops promotes open access. Past workshop content is available under a Creative Commons License.


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