1. Canadian Bioinformatics Workshops

2. Module #: Title of Module2

3. Module 4 Network Visualization and Analysis Enrichment Map
Gary Bader
Pathway and Network Analysis for –omics Data
July 7-8, 2011

4. Enrichment Test: General Framework
Experimental
Data
Enrichment Table
Spindle
Apoptosis
ENRICHMENT
TEST
Gene-set
Databases

5. Excellent idea used to interpret data in thousands of papers
GO.id GO.name p.value covercover.rat Deg.mdn Deg.iqr
GO: taxis E
GO: chemotaxis E
GO: adaptive immune response based on somatic recombination E
GO: adaptive immune response E
GO: leukocyte mediated immunity
GO: B cell mediated immunity
GO: myeloid cell differentiation
GO: immune effector process
GO: regulation of phagocytosis
GO: positive regulation of phagocytosis
GO: lymphocyte mediated immunity
GO: growth factor binding
GO: protein polymerization
GO: endoplasmic reticulum membrane
GO: immunoglobulin mediated immune response
GO: heart development
GO: response to bacterium
GO: regulation of endocytosis
GO: acute inflammatory response
GO: positive regulation of endocytosis
GO: myeloid leukocyte activation
GO: amino acid biosynthetic process
GO: regulation of inflammatory response
GO: activation of immune response
GO: positive regulation of immune system process
GO: positive regulation of immune response
GO: antigen processing and presentation
GO: regulation of immune system process
GO: regulation of immune response
GO: negative regulation of enzyme activity
GO: phagocytosis
GO: myeloid leukocyte differentiation
GO: humoral immune response
GO: lymphocyte activation
GO: leukocyte chemotaxis
GO: negative regulation of protein kinase activity
GO: negative regulation of transferase activity
GO: transforming growth factor beta receptor signaling pathw
GO: insulin-like growth factor binding
GO: T cell activation
GO: humoral immune response mediated by circulating immunogl
GO: cytosolic ribosome (sensu Eukaryota)

6. Excellent idea used to interpret data in thousands of papers
But! Major cognitive burden relating overlapping gene sets
GO.id GO.name p.value covercover.rat Deg.mdn Deg.iqr
GO: taxis E
GO: chemotaxis E
GO: adaptive immune response based on somatic recombination E
GO: adaptive immune response E
GO: leukocyte mediated immunity
GO: B cell mediated immunity
GO: myeloid cell differentiation
GO: immune effector process
GO: regulation of phagocytosis
GO: positive regulation of phagocytosis
GO: lymphocyte mediated immunity
GO: growth factor binding
GO: protein polymerization
GO: endoplasmic reticulum membrane
GO: immunoglobulin mediated immune response
GO: heart development
GO: response to bacterium
GO: regulation of endocytosis
GO: acute inflammatory response
GO: positive regulation of endocytosis
GO: myeloid leukocyte activation
GO: amino acid biosynthetic process
GO: regulation of inflammatory response
GO: activation of immune response
GO: positive regulation of immune system process
GO: positive regulation of immune response
GO: antigen processing and presentation
GO: regulation of immune system process
GO: regulation of immune response
GO: negative regulation of enzyme activity
GO: phagocytosis
GO: myeloid leukocyte differentiation
GO: humoral immune response
GO: lymphocyte activation
GO: leukocyte chemotaxis
GO: negative regulation of protein kinase activity
GO: negative regulation of transferase activity
GO: transforming growth factor beta receptor signaling pathw
GO: insulin-like growth factor binding
GO: T cell activation
GO: humoral immune response mediated by circulating immunogl
GO: cytosolic ribosome (sensu Eukaryota)

7. Enrichment Map http://baderlab.org/Software/EnrichmentMap/ GENE SETS
Spindle
Ca++ Channels
Gene.A
Gene.B
Gene.C
Gene.G
Gene.H
Gene.I
Apoptosis
MAPK
Gene.D
Gene.E
Gene.F
Gene.L
Gene.M
Gene.N
Use available gene-set scoring models
threshold dependent (e.g. Fisher’s) or threshold free (e.g. GSEA)
Use the network framework to organize gene-sets exploiting their inter-dependencies

8. Gene Set Enrichment Analysis (GSEA)
Ranked Gene List UP
(A > B)
GSEA
DOWN
(B > A)
Gene-sets

9. Enrichment Map
Overlap

10. Enrichment Map: use case I Single enrichment
Estrogen treatment of breast cancer cells
Design:
2-time points, two-class
Gene set Database:
Gene Ontology
12 hrs
24 hrs
Estrogen-treated 3
Untreated

13. Enrichment Map: use case II Comparison of two enrichments
Estrogen treatment of breast cancer cells
Design:
2-time points, two-class
Gene set Database:
Gene Ontology
12 hrs
24 hrs
Estrogen-treated 3
Untreated

16. Enrichment Map: use case III Query Set Analysis

17. Pathways Enriched in Autism Spectrum Disorder
Pinto et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature Jun 9.

19. Gene-set sources Gene Ontology Pathways PFAM domains
Biological Process
Cellular Component
Molecular Function
Pathways
KEGG
NCI
Reactome
PFAM domains
Number of gene-sets:
Unfiltered (all): 14,433
Filtered (5 << 700 genes): 6,129
Tested (counts > 0): 3,493
Pinto et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature Jun 9.

21. Future Work Isserlin et al. , Proteomics 2010
Add network visualization support
Pathway visualization and analysis tools
Isserlin et al. , Proteomics 2010

22. http://baderlab.org/Software/WordCloudPlugin Layla Oesper
Cluster words according to their co-occurrence in labels to preserve semantic meaning.
Layla Oesper
Google Summer of Code

24. Enrichment Map Lab
Try out enrichment map – load the plugin from the plugin manager
Load DAVID results – or - load the GSEA enrichment analysis file - EM_EstrogenMCF7_TestData.zip (unzip) available at