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NetBioSIG2012 ugurdogrusoz-cbio
- 1. Network Visualization and Analysis in the cBio Cancer Genomics Portal U. Dogrusoz, S.O. Sumer, S. Sonlu, J. Gao, B.A. Aksoy, B.E. Gross, N. Schultz, E. Cerami, C. Sander
- 2. cBio Cancer Genomics Portal Goal: Make complex genomic data available through an intuitive interface Allow explorative data analysis / hypothesis testing / visualization Cerami et al. 2012, Cancer Discovery
- 4. cBio Cancer Genomics Portal Cerami et al. 2012, Cancer Discovery
- 5. Workflow of network analysis
- 6. Pathway Commons Cerami et al 2010, Nucl Acids Res
- 7. Workflow of network analysis
- 8. Hairball Problem Complete network for TP53, MDM2, MDM4 & CDKN2A (463 interacting neighbors) This complete network can be downloaded in SIF or GraphML in cBio Portal.
- 9. Pre-filtered network based on alteration frequencies The network below contains 54 nodes, including your 4 query genes and the 50 most frequently genes out 463 altered neighbor genes(out of 463). Query genes: CDKN2A MDM2 MDM4 TP53
- 10. Workflow of network analysis
- 11. Genomic data overlaid on interaction network
- 12. Genomic data overlaid on interaction network Alteration frequency: the % of samples that were altered on the gene
- 13. Genomic data overlaid on interaction network Color gradient •white to red •based on alteration frequency Genomic data •mutation •copy number •mRNA expression
- 14. Further filtering by genomic alterations Filter genes by alteration frequency Slide to threshold Or type value threshold value
- 15. Further filtering by genomic alterations Gene with total alteration frequency 12% or less filtered out
- 16. Filtering by genes of interest Hide selected genes from the network Search genes by name Select genes from canvas or gene list under Genes tab
- 17. Filtering by interaction type & source Interactions Interactions merged by default Type (color-coded) & source shown in interaction details Shown individually
- 18. Filtering by interaction type & source
- 19. Filtering by interaction type & source
- 20. Automatic network layout Change layout Recalculate options layout Recalculate layout after filtering
- 21. Iterative network analysis Re-submit selected genes to the portal
- 22. Drugs of New cBioPortal features specified genes Drug – gene targeting • Data source is DrugBank database of detail: Level (http://www.drugbank.ca) -None Inspect details targeting specified-FDA approved only • Only drugs genes shown including: -All -Targeted genes -Corresponding DrugBank page
- 23. Other new cBioPortal features Network visualization service for IGV • Glioblastoma, RB pathway
- 24. Other new cBioPortal features Cross-cancer query
- 25. Other new cBioPortal features Oncoprint improvements Protein/phosphoprotein Mutation details event call
- 26. Other new cBioPortal features Mutation diagram
- 27. Other new cBioPortal features Many new cancer studies • 21 (5 of them published, rest provisional) cancer studies
- 28. Work in progress and future plans • SBGN-compliant viewer (GSoC) – Networks presented in SBGN Process Description language • Construct Network-of-Interest from Genes-of- Interest using linker paths (Dogrusoz et al, 2009, BMC Bioinf) • Roundtrip analysis (query, modify, re-query, …) • Better/incremental layout • Use Cytoscape Web 2 (html5 version)
- 29. Acknowledgements • Bilkent University • MSKCC – S. Onur Sumer – S. Onur Sumer – Sinan Sonlu – Jianjiong Gao – Naim Kucukdemirci – B. Arman Aksoy – Istemi Bahceci – Benjamin E. Gross – Nikolaus Schultz – Ethan Cerami – Chris Sander
Notas del editor
- B) The RB Oncoprint, alterations of genes in this pathway tend to be mutually exclusiveC) Many RB1 mutations may have strong functional consequences as predicted by MutationAccessor.orgD) CDK4 mRNA expression is elevated in amplified casesE) Cases with an RB pathway alteration have worse overall survival than cases without an RB pathway alterationF) Network tab provides interactive analysis and visualization of networks altered in the chosen cancer study
- The network of interest built from genes of interest consists of pathways and interactions derived from the open-source Pathway Commons project.
- PC provides a central, convenient point of access to multiple publicly available pathway and interaction databases. It does so by integrating data sources formatted in the BioPAX or PSI–MI standards, and making all data sets available via a unified web site, a single web service interface and a batch download site.
- Glioblastoma: TP53 Pathway (4 genes)
- Links to IGV for visualization of DNA copy-number changes (through Web Start)
- Links to IGV for visualization of DNA copy-number changes (through Web Start)
- Cross-cancer functionality enables users to query across all cancer studies in our database
- OncoPrints are compact means of visualizing distinct genomic alterations, including somatic mutations, copy number alterations, and mRNA expression changes across a set of cases. They are extremely useful for visualizing gene set and pathway alterations across a set of cases, and for visually identifying trends, such as trends in mutual exclusivity or co-occurence between gene pairs within a gene set. Individual genes are represented as rows, and individual cases or patients are represented as columns.
- Mutation Diagrams show mutations in the context of protein domains.