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Tutorial session 3 Network analysis Exploring PPI networks using Cytoscape EMBO Practical Course Session 8 Nadezhda Doncheva and Piet Molenaar Overview Focus: Network analysis Identify active subnetworks Analyze Gene Ontology enrichment Perform topological analysis Find network clusters Find network motifs Concepts Enrichment Clustering Guild by association Data 2 Stored sessions; Drosophila and Neuroblastoma 5/23/2017 Identify active subnetworks jActiveModules plugin Active modules are sub-networks that show differential expression over user-specified conditions or time-points Microarray gene-expression attributes Mass-spectrometry protein abundance Input: interaction network and p-values for gene expression values over several conditions Output: significant sub-networks that show differential expression over one or several conditions 3 5/23/2017 jActiveModules (Demo) 4 5/23/2017 Use case; Assignment 3.1 Using neuroblastoma cell lines inhibitors to elucidate important pathways 2 neuroblastoma cell lines: SHEP21, SY5Y 7 inhibitors Profiled on Affymetrix array 5 http://r2.amc.nl Other resource e.g. GEO 5/23/2017 Use case; Assignment 3.1 Systematic perturbations Different cell-lines Including controls: DMSO 97 arrays: data collected from R2: hugo-once etc PI3K-dependent Cell lines -SY5Y -D425 PIK90 RAS/ERK-dependent Cell lines -SHEP2 -RD Harvest: RNA Affy (97samples) protein WB PI3K signature RAS/ERK signature RAS RAF U0126 PI3K PI103 AKTi 1/2 MK2206 AKT MEK mTORC1 mTORC2 ERK Rapamycin PP242 Use case; Assignment 3.1 1. Open the Neuroblastoma session and load the pvalues from this experiment 2. Run jActiveModules on the annotated network 7 1. What regions are important? 2. Can you imagine any caveats for this method? 5/23/2017 Gene Ontology Provides three structured controlled vocabularies (ontologies) of defined terms representing gene product properties: 8 Biological Process (23074 terms): biological goal or objective Molecular Function (9392 terms): elemental activity/task Cellular Component (2994 terms): location or complex 5/23/2017 Analyze Gene Ontology enrichment BiNGO plugin: http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html Calculates over-representation of a subset of genes with respect to a background set in a specific GO category Input: subnetwork or list, background set by user Output: tree with nodes color reflecting overrepresentation; also as lists Caveats: Gene identifiers must match; low GO term coverage, background determining 9 5/23/2017 BiNGO (Demo) 10 5/23/2017 Use case; Assignment 3.2 Open the Neuroblastoma session and run BiNGO on the filtered network. 1. 1. What categories are enriched? 2. Can you find these back in the article? 11 5/23/2017 Compute topological parameters NetworkAnalyzer plugin: http://med.bioinf.mpiinf.mpg.de/netanalyzer/ Computes a comprehensive set of simple and complex topological parameters Displays the results in charts, which can be saved as images or text files Can be combined with the ShortestPath plugin http://www.cgl.ucsf.edu/Research/cytoscape/shortestPath/i ndex.html 12 5/23/2017 NetworkAnalyzer (Demo) 13 5/23/2017 Identify hubs CytoHubba plugin: http://hub.iis.sinica.edu.tw/cytoHubba/ Computes several topological node parameters Identifies essential nodes based on their score and displays them in a ranked list Generates a subnetwork composed of the best-scored nodes 14 5/23/2017 CytoHubba (Demo) 15 5/23/2017 Use case; Assignment 3.3 Open the Drosophila network session Check the network parameters 1. 1. Is it scale free? 2. Can you find important players? 16 5/23/2017 Find network clusters Network clusters are highly interconnected sub-networks that may be also partly overlapping Clusters in a protein-protein interaction network have been shown to represent protein complexes and parts of biological pathways Clusters in a protein similarity network represent protein families Network clustering is available through the MCODE Cytoscape plugin: http://baderlab.org/Software/MCODE 17 5/23/2017 MCODE & ClusterMaker (Demo) 18 5/23/2017 Use case; Assignment 3.4 Open the Drosophila session 1. Run the MCODE algorithm 2. Run the MCL clustering algorithm 1. Compare the results 2. Can you corroborate some of the clusters found in the article? 3. Are there additional filtering options? 4. Play with the settings and observe their influence 19 5/23/2017 Find network motifs NetMatch plugin: http://alpha.dmi.unict.it/~ctnyu/netmatch.html Network motif is a sub-network that occurs significantly more often than by chance alone Input: query and target networks, optional node/edge labels Output: topological query matches as subgraphs of target network Supports: subgraph matching, node/edge labels, label wildcards, approximate paths 20 5/23/2017 NetMatch (Demo) 21 5/23/2017 Use case; Assignment 3.5 1. In the Drosophila session try to find a feedforward motif 2. Finally toy around with the settings of the Vizmapper to produce a nice paper-ready figure! 22 5/23/2017 Other Useful Plugins PSICQUICUniversalClient AgilentLiteratureSearch GeneMANIA CyThesaurus 23 structureViz ClusterMaker EnrichmentMap PiNGO ClueGO RandomNetworks 5/23/2017 Wrapping up… Biological questions I have a protein I have a list of proteins Function, characteristics from known interactions Shared features, connections I have data Derive causal networks Network 24 Topology Hubs Clusters New hypotheses 5/23/2017 End! And a final note….. 25 5/23/2017 Announcing Cytoscape 3.0 Beta Easier data import Improved user experience Graphical annotations One-click install from AppStore Improved API for app developers http://cytoscape.org