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  Stored sessions; Drosophila and Neuroblastoma 11/1/20152

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 11/1/20153

jActiveModules (Demo) 11/1/20154

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   Other resource e.g. GEO 11/1/20155

Use case; Assignment 3.1  Systematic perturbations  Different cell-lines  Including controls: DMSO  97 arrays: data collected from R2: hugo-once etc PI3K signature RAS/ERK signature RAS/ERK-dependent Cell lines -SHEP2 -RD PI3K-dependent Cell lines -SY5Y -D425 Harvest: RNA  Affy (97samples) protein  WB PI3K AKT mTORC1 mTORC2 RAS MEK RAF ERK PI103 PP242 PIK90 Rapamycin U0126 AKTi 1/2 MK2206

Use case; Assignment Open the Neuroblastoma session and load the pvalues from this experiment 2. Run jActiveModules on the annotated network 1. What regions are important? 2. Can you imagine any caveats for this method? 11/1/20157

Gene Ontology  Provides three structured controlled vocabularies (ontologies) of defined terms representing gene product properties:  Biological Process (23074 terms): biological goal or objective  Molecular Function (9392 terms): elemental activity/task  Cellular Component (2994 terms): location or complex 11/1/20158

Analyze Gene Ontology enrichment  BiNGO plugin:  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 11/1/20159

BiNGO (Demo) 11/1/201510

Use case; Assignment Open the Neuroblastoma session and run BiNGO on the filtered network. 1. What categories are enriched? 2. Can you find these back in the article? 11/1/201511

Compute topological parameters  NetworkAnalyzer plugin: inf.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 ndex.html 11/1/201512

NetworkAnalyzer (Demo) 11/1/201513

Identify hubs  CytoHubba plugin:  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 11/1/201514

CytoHubba (Demo) 11/1/201515

Use case; Assignment 3.3  Open the Drosophila network session 1. Check the network parameters 1. Is it scale free? 2. Can you find important players? 11/1/201516

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: 11/1/201517

MCODE & ClusterMaker (Demo) 11/1/201518

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 11/1/201519

Find network motifs  NetMatch plugin:  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 11/1/201520

NetMatch (Demo) 11/1/201521

Use case; Assignment 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! 11/1/201522

Other Useful Plugins  PSICQUICUniversalClient  AgilentLiteratureSearch  GeneMANIA  CyThesaurus  structureViz  ClusterMaker  EnrichmentMap  PiNGO  ClueGO  RandomNetworks 11/1/201523

Wrapping up…  Biological questions  I have a protein  Function, characteristics from known interactions  I have a list of proteins  Shared features, connections  I have data  Derive causal networks  Network  Topology  Hubs  Clusters 11/1/ New hypotheses

End! And a final note….. 11/1/201525

Announcing Cytoscape 3.0 Beta  Easier data import  Improved user experience  Graphical annotations  One-click install from AppStore  Improved API for app developers