1. Reactome pathway knowledgebase Connecting pathways, networks, and disease Robin Haw, PhD Project Manager and Outreach Coordinator Ontario Institute for Cancer Research robin.haw@oicr.on.ca San Diego. March 15, 2016

2. BIG data & Genomics Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, et al. (2015) Big Data: Astronomical or Genomical?. PLoS Biol 13(7): e1002195. doi:10.1371/journal.pbio.1002195 http://journals.plos.org/plosbiology/article?id=info:doi/10.1371/journal.pbio.1002195

3. Motivation for Pathway Databases and Analysis Intuitive display for biological and chemical data. Visualize multiple data types on a pathway. Computational methods available to automate analysis. Pathway Databases satisfy common “use cases”: Identifying hidden patterns in gene lists. Creating mechanistic models to explain experimental observations. Predicting the function of unannotated genes. Establishing the framework for quantitative modeling. Assisting in the development of molecular signatures.

4. Pathway Analysis Pipeline Khatri et al. PLOS Comp Bio. 8:1 2012

5. Open source and open access pathway database 1900+ pathway modules encompassing many areas of human biology. Expert authored, manually curated and peer-reviewed. Every pathway is traceable to primary literature. Extensively cross-referenced to external bio- and chemoinformatics databases. Computationally inferred pathways for 18 model organisms. Provides tools and datasets for browsing and visualizing pathway data. www.reactome.org What is Reactome?

6. Reactome is a Reaction Network Database –explicitly describe biological processes as a series of biochemical reactions and events –represents many events and states found in biology. The Unit of Reactome

7. Reaction and Pathway Coverage Metabolism (Anabolic, Catabolic, Xenobiotic, etc) Signal Transduction (EGFR, Notch, Wnt, etc.) Developmental Biology (Axon Guidance, Myogenesis) Cell Cycle DNA Damage & Repair Stress Response Disease (Metabolic Disorder, Cancer, etc) Phosphorylation Metabolic

8. Pathway Browser

9. Balanced Reactions from Rhea

10. Protein and Chemical Structures

11. PSICQUIC Interaction Overlay

12. Expression Data from Gene Expression Atlas

13. Pathway Diagrams support Reactome Tools Pathway Mapping and Enrichment Analysis What pathways are represented in my dataset? Is my dataset enriched with proteins from a pathway? Expression Overlay onto Pathways Which pathways are expressed in my dataset? Compare Species What pathways are shared between humans and model organisms? External Data Linkages (linkouts to ZINC & ChEMBL) For each compound, is it commercially available or an analog is purchasable? For each protein target, what compounds are known and purchasable?

14. Standard graphical languages for representing biological processes and interactions SBML level 2.4 Open access interchange format for computer models of biochemical pathways, reactions and networks. PSICQUIC is an effort to standardize the access to molecular interaction databases. PSI-MITAB is the data exchange format. BioPAX level 2 & 3. Standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. BioPAX Interoperability through Open Data Standards

15. Analyzing mutated genes in a network context: reveals relationships among these genes can elucidate mechanism of action of drivers facilitates hypothesis generation on roles of these genes in disease phenotype Network analysis reduces hundreds of mutated genes to < dozen mutated pathways Network Module-based Analysis of Disease OMICS data

16. ReactomeFIViz Cytoscape App Extract and Cluster, and Annotate Altered Genes Disease “modules” (10-30) Curated Pathway DBs Uncurated Interaction Evidence + Reactome Functional Interaction Network (~12K proteins; ~328K interactions) Machine Learning Cytoscape using ReactomeFIViz app Project your data into Reactome FI Network + A human functional protein interaction network and its application to cancer data analysis, Wu et al. 2010 Genome BiologyWu et al. 2010 Genome Biology

17. ReactomeFIViz Analysis TCGA Breast Cancer Mutations [NCI MAF (mutation annotation file)] Signaling by Tyrosine Kinase receptors NOTCH and Wnt signaling Cadherin signaling Focal adhesion ECM-Receptor interaction Signaling by Rho GTPases Axon guidance Mucin cluster Neuroactive ligand-receptor interaction Calcium signaling Ubiquitin-mediated proteolysis M phase G2/M Transition Metabolism of proteins DNA repair Cell cycle Cell adhesion molecules Clustering and Annotating of TCGA Breast Cancer Mutations

18. Conclusions Reactome is a highly reliable, curated database of biological pathways. Web site provides tools and datasets for visualizing pathway data and interpreting your experimental data. ReactomeFIViz app provides a powerful way to visualize and analyze cancer and disease data sets. All data and software are open to public; no licensing required.

19. Acknowledgements Eric Dawson Antonio Fabregat Mundo Phani Garapati Marc Gillespie Bijay Jassal Steve Jupe Bruce May Lisa Matthews Marija Orlic-Milacic Karen Rothfels Veronica Shamovsky Konstantinos Sidiropoulos Guilherme Viteri Joel Weiser Marissa Webber Guanming Wu Henning Hermjakob Peter D’Eustachio Lincoln Stein