Network Analysis Workshop

Systems Biology Analysis Methods for Genomic Data, 15 July -19 July 2013

Organizers Steve Horvath, Jenny Papp University of California, Los Angeles

Department of Human Genetics and Biostatistics, University of California, Los Angeles

Lecture Notes



This five full-day intensive course will cover network analysis methods widely used in systems biologic and systems genetic applications. The goal of the network analysis workshop is to familiarize researchers with network methods and software for integrating genomic data sets with complex phenotype data. Participants will learn how to integrate disparate data sets (genetic variation, gene expression, protein interaction networks, complex phenotypes, gene ontology information) and use networks for identifying disease genes, pathways and key regulators.


Topics covered

1.      CourseSchedule7.docx

2.      Weighted Network Analysis and Weighted Gene Co-Expression Network Analysis

3.      Pathway Analysis and Network Visualization

4.      Network Biology in Neuroscience and Neuropsychiatric Disease

5.      Network-based Meta-Analyses of Multiple Data Sets

6.      Causal Inference and Integrative Bayesian Network Approaches to Disease Models

7.      Systems Genetics for Experimental Crosses

8.      Brief intro to Structural equation models

9.      Meta analysis methods

10.  Random generalized linear model predictor


1.      Steve Horvath, UCLA

2.      Gary Bader, University of Toronto

3.      Elias Chaibub Neto, Sage Bionetworks

4.      Michael Hawrylycz, Allen Institute for Brain Science

5.      Peter Langfelder, UCLA

6.      Jeremy Miller, Allen Institute for Brain Science

7.      Brian Yandell, University of Wisconsin

8.      Bin Zhang, Mount Sinai School of Medicine

9.      Jun Zhu, Mount Sinai School of Medicine

Steve Horvath: lecture notes

1.      Talk1OverviewWGCNAHorvath.ppt youtube:

2.      Talk2PreservationHorvath.ppt youtube:

3.      Talk3SystemsGeneticsHorvath.ppt youtube:

4.      Talk4EmpiricalEvaluationHorvath.pptx youtube: (only slides 1 to 40)

5.      Talk5MetaAnalysisDifferentialNetworkAnalysis.ppt youtube:

6.      Talk6randomGLMHorvath.pptx Youtube:

R software tutorials from Steve Horvath

1.      WGCNA tutorial, corrected book chapter 12 youtube:

2.      Random GLM predictor Youtube:

Peter Langfelder: lecture notes

1.      LectureHierarchicalClusteringLangfelder1.pdf youtube:

2.      LectureconsensusModulesLangfelder2.pdf  youtube


Gary Bader: lecture notes

1.      Bader1_NetworkVisualization&Analysis.ppt  youtube

2.      Bader2_ProteinSequence&Cancer.ppt youtube:

3.      Cytoscape Wall of Apps

Jeremy Miller: lecture notes

1.      Miller1_ComparingMouseAndHumanBrain.pdf youtube:

2.      Miller2_NetworksInTheBrain.pdf youtube:

3.      Miller3_NetworkVisualization_and_EnrichmentAnalysis.pdf youtube:

4.      Example Tutorial

5.      Updated tutorials from J Miller

Brian Yandell: lecture notes

1.      Yandell1_MultTrait.pdf youtube:

2.      Yandell2_HotSpot.pdf youtube:

3.      Yandell3_InstallQTL.pdf

4.      Yandell4_Tutorial.pdf youtube:

Elias Chaibub Neto: lecture notes

1.      Neto_CausalGraphicalModels.pdf youtube:

Bin Zhang: lecture notes

2.      Zhang_Lecture1_Mutiscale-Networks.pdf youtube:

3.      Zhang_Lecture2_KeyDriverAnalysis.pdf youtube:

4.      Zhang_Lecture3_AD-Networks.pdf

5.      Zhang_Lecture4_Demo.pdf youtube:

Jun Zhu

1.      Zhu1_BayesianNetwork_Intro.pdf youtube:

2.      Zhu2_BayesianNetwork_dataIntegration.pdf youtube:

Background Material & Useful Links

  1. Installing R/qtl-related packages
  2. Installing the WGCNA R package
  3. Background material on weighted networks
  4. RCytoscape: Tools for Molecular Cartography
  5. Install Cytoscape
  6. Introductory tutorial to Cytoscape (see Introduction parts 1 & 2)
  7. For more preparatory readings on Cytoscape click here and here
  8. Bioconductor
  9. Allen Institute for Brain Science
  10. R/qtlyeast
  11. For background material on causal testing/systems genetics click here, here and here


Picture of participants









Email: shorvath /at/

for course info: statgene /at/


This workshop was supported by NIH grant 1R25GM103774-01 and hosted by UCLA

Other material regarding weighted gene co-expression network analysis

             Weighted Gene Co-Expression Network Page



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